diff --git a/docs/knowledge-base.md b/docs/knowledge-base.md
index 197b7eef6..7a6b9c36a 100644
--- a/docs/knowledge-base.md
+++ b/docs/knowledge-base.md
@@ -14,7 +14,7 @@ separate work, not an implemented capability of this knowledge base.
 ```text
 src/inferrsi/data/skill_library/
   README.md                         Library navigation
-  skill-index.json                   Stable IDs → categorized paths/backend (74 skills)
+  skill-index.json                   Stable IDs → categorized paths/backend (76 skills)
   hardware/{ascend,cuda,host}/<id>/   Hardware/platform-specific complete skills
   frameworks/<framework>/<id>/      Framework-owned complete skills
   repositories/<repo>/              Engine entry, sub-skills and focused complete skills
@@ -166,23 +166,23 @@ standalone export: retain the declared dependencies or the complete library.
 
 All 48 former root skills now have one canonical home under
 [`src/inferrsi/data/skill_library/`](../src/inferrsi/data/skill_library/README.md).
-Complete procedures, sidecars, references and cases are packaged, with 13 Ascend,
+Complete procedures, sidecars, references and cases are packaged, with 14 Ascend,
 3 CUDA and 5 host skills under `hardware/`; the rest are grouped as frameworks,
 repositories, methods or workflows. The 21 engine and research-router skills
 use the same ownership layout under `repositories/<engine>/` and
 `workflows/inference-engine-research/`, including their sub-skills and references.
-The library contains 119 `SKILL.md` files, all in English.
+The library contains 120 `SKILL.md` files, all in English.
 The collection overview, import notes and source manifest belong to the research
 workflow's references; Strata design-space analysis belongs to Strata. The library
 root contains only navigation and the registry.
 
 The [generated catalog](../src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md)
-projects the 75 registered skills into the contribution catalog. Its records
+projects the 76 registered skills into the contribution catalog. Its records
 use `inferrsi.<backend>.skills.<name_with_underscores>` IDs, with `ascend` and
 `cuda` for scopes that depend on those backends and `common` for the remaining skills.
 Each `skill_documents.original` points to the full packaged procedure. The
 `skills` CLI retains the original hyphenated skill IDs and defaults to this
-75-ID registry; engine procedures remain available through library navigation
+76-ID registry; engine procedures remain available through library navigation
 and catalog document pointers.
 
 The registered [h3.c runtime audit](../src/inferrsi/data/skill_library/repositories/h3-c/audit-h3-runtime-residency/SKILL.md)
diff --git a/docs/skill-coverage.md b/docs/skill-coverage.md
index ad7373d6a..91de26e70 100644
--- a/docs/skill-coverage.md
+++ b/docs/skill-coverage.md
@@ -4,7 +4,7 @@ Generated from the registry, the skill sidecars and the two maintained
 matrices. **Do not edit by hand**; regenerate after any registry, skill,
 matrix or frozen-plan change.
 
-- Input digest: `sha256:cb1fedb4292b272ef63223dd29fa1fc483c63cd0cee74397ad7aa17dbf3a5321`
+- Input digest: `sha256:61b440f9e3333b2ad1e1aac0b9808b1610e389e0a96c151f38d3df931758daed`
 - Regenerate: `python tools/build_skill_coverage.py`
 - Verify without writing: `python tools/build_skill_coverage.py --check`
 
@@ -31,16 +31,16 @@ matrix: every field is copied from an owner that already maintains it.
 
 | Measure | Value |
 |---|---|
-| Registered skill ids | 75 |
-| By category | frameworks 3, hardware 22, methods 19, repositories 25, workflows 6 |
-| By backend | ascend 14, common 56, cuda 5 |
+| Registered skill ids | 76 |
+| By category | frameworks 3, hardware 22, methods 20, repositories 25, workflows 6 |
+| By backend | ascend 14, common 57, cuda 5 |
 | Recorded on a numbered SearchSpace resource layer | 48 |
 | Recorded only in a supplementary guidance table (†) | 13 |
 | Recorded on two or more resource layers | 24 |
 | Recorded in the Reference Matrix | 68 |
-| With a `metadata.json` sidecar | 70 |
+| With a `metadata.json` sidecar | 71 |
 | Selected by a frozen evaluation plan | 2 |
-| `SKILL.md` documents in the library | 119 |
+| `SKILL.md` documents in the library | 120 |
 | Unregistered documents (excluded from every count above) | 44 |
 
 A complete inventory is not a coverage claim. Every registered row below
@@ -60,7 +60,7 @@ optimization is fully covered or that any procedure has measured benefit.
 | [ascend-operator-tuning](../src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/SKILL.md) | ascend | Run a staged, accuracy-gated tuning campaign on a single Ascend NPU operator: set a numeric target up front, block ... | 1 Accelerator · Optimize | 1 · Systems sources (ascend-ai-coding/awesome-ascend-skills @ 75ec89c) | candidate · not_run · 0 readset(s) | no-eval |
 | [ascend-optimization-casebook](../src/inferrsi/data/skill_library/hardware/ascend/ascend-optimization-casebook/SKILL.md) | ascend | Casebook of NPU optimization cases for Ascend inference systems: symptom → diagnosis → action → evidence records for ... | 1 Accelerator · Optimize / Verify | 1 · Systems sources (Ascend/MindIE-SD @ 8481d39) | candidate · not_run · 0 readset(s) | no-eval |
 | [ascend-performance-analysis](../src/inferrsi/data/skill_library/hardware/ascend/ascend-performance-analysis/SKILL.md) | ascend | Diagnose performance bottlenecks on Ascend NPU systems using CANN profiling data. Maps GPU profiling concepts (nsys ... | 1 Accelerator · Observe / Profile / Diagnose / Verify<br>4 Network · Observe / Profile / Diagnose / Verify<br>5 OS · Diagnose | 1 · Systems sources (Ascend/MindIE-SD @ 8481d39)<br>1 · Systems sources (cann/cannbot @ `c0e2ad23ee1a73e3c0f84c8df1cc459e2aae3110` (selected ...) | candidate · not_run · 1 readset(s) | no-eval |
-| [ascend-video-diffusion-optimization](../src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/SKILL.md) | ascend | Run and verify goal-driven Ascend video diffusion optimization. Use when the user asks for latency, RTF, throughput, or ... | — | — | candidate · not_run · 1 readset(s) | no-SearchSpace-layer, no-Reference-Matrix-row, no-eval |
+| [ascend-video-diffusion-optimization](../src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/SKILL.md) | ascend | Run and verify goal-driven Ascend video diffusion optimization. Specializes the backend-agnostic ... | — | — | candidate · not_run · 1 readset(s) | no-SearchSpace-layer, no-Reference-Matrix-row, no-eval |
 | [ascendc-tiling-design](../src/inferrsi/data/skill_library/hardware/ascend/ascendc-tiling-design/SKILL.md) | ascend | Design tiling for a custom AscendC operator: normalize the shape first (axis-collapse or flatten), answer the ... | 1 Accelerator · Optimize | 1 · Systems sources (ascend-ai-coding/awesome-ascend-skills @ 75ec89c) | candidate · not_run · 0 readset(s) | no-eval |
 | [cann-attribution-overlap](../src/inferrsi/data/skill_library/hardware/ascend/cann-attribution-overlap/SKILL.md) | ascend | Attribute NPU trace kernels to model source and plan bounded multistream overlap: select a representative step, map ... | 1 Accelerator · Observe / Profile / Diagnose / Optimize / Verify<br>4 Network · Diagnose / Optimize / Verify | 1 · Systems sources (cann/oam-tools @ `8440935f` (!302 import; later master `f3cf4115` ...) | candidate · not_run · 0 readset(s) | no-eval |
 | [cgroup-resource-controls](../src/inferrsi/data/skill_library/hardware/host/cgroup-resource-controls/SKILL.md) | common | Diagnose and configure cgroup v2 resource controls for serving/training workloads: distinguish quota stalls from ... | 2 RAM/Host · Observe / Profile / Configure / Verify<br>5 OS · Observe / Profile / Diagnose / Configure / Optimize / Verify | 1 · Systems sources (Linux cgroup v2 docs — kernel.org live 2026-10-15 (revision ...) | candidate · not_run · 0 readset(s) | no-eval |
@@ -112,7 +112,7 @@ optimization is fully covered or that any procedure has measured benefit.
 | [splash](../src/inferrsi/data/skill_library/repositories/splash/SKILL.md) | common | Investigate Splash model-format compatibility, automatic memory planning, Metal and ANE execution, DFlash2 ... | — | Splash portable AREX extraction (incoai/splash @ `39a97385f8560cf8a93972cec9b0a963c9195250`; AREX ...) | candidate · partial_cpu_only · 2 readset(s) | no-SearchSpace-layer, no-eval |
 | [vllm-metal](../src/inferrsi/data/skill_library/repositories/vllm-metal/SKILL.md) | common | Investigate vllm-metal Apple inference through platform and native-ABI selection, paged KV/offload ownership ... | 1 Accelerator † guidance: vLLM Metal selected source contracts<br>2 RAM/Host † guidance: vLLM Metal selected source contracts<br>3 SSD † guidance: vLLM Metal selected source contracts | vLLM Metal portable AREX source and CPU extraction (vllm-project/vllm-metal @ `e7df7a6ff215f99c7842552d230fdbc709835934` ...) | candidate · partial_cpu_only · 2 readset(s) | no-eval |
 
-## Registered: Methods (19)
+## Registered: Methods (20)
 
 | Skill | Backend | Declared task | SearchSpace layer / stage | Reference Matrix | State | Gaps |
 |---|---|---|---|---|---|---|
@@ -134,6 +134,7 @@ optimization is fully covered or that any procedure has measured benefit.
 | [skill-evolution-playbook](../src/inferrsi/data/skill_library/methods/skill-evolution-playbook/SKILL.md) | common | Practical design choices for evolving agent skills from execution traces: when one trajectory should update a skill ... | — | 2 · Methodology and corpus references (Qwen-Applications/Trace2Skill @ 3d0b52a)<br>2 · Methodology and corpus references (microsoft/SkillOpt @ 343db22) | candidate · not_run · 0 readset(s) | no-SearchSpace-layer, no-eval |
 | [training-input-pipeline](../src/inferrsi/data/skill_library/methods/training-input-pipeline/SKILL.md) | common | Diagnose training input stalls and choose bounded queue, shard-cache and cache-ownership changes from DALI, Mosaic ... | 1 Accelerator · Observe / Configure / Optimize<br>2 RAM/Host · Observe / Diagnose / Configure / Optimize<br>3 SSD · Diagnose / Configure / Optimize<br>4 Network · Configure / Optimize<br>5 OS · Configure / Optimize | 1 · Systems sources (B1 / NVIDIA DALI @ `6fe47c48d3b0ca335f5e1afd3c77c750b2c7e041` ...)<br>1 · Systems sources (B2 / Mosaic Streaming @ `d99bf9c7cdf2dd4ed62a4960ed35270b93337a5f` ...)<br>1 · Systems sources (B3 / FFCV @ `3a12966b3afe3a81733a732e633317d747bfaac7` ...) | candidate · not_run · 1 readset(s) | no-eval |
 | [training-resource-budget](../src/inferrsi/data/skill_library/methods/training-resource-budget/SKILL.md) | common | Choose training offload and resource-budget changes using pinned DeepSpeed configuration, attributed expert diagnosis ... | 1 Accelerator · Diagnose / Configure / Optimize<br>2 RAM/Host · Observe / Diagnose / Configure / Optimize / Verify<br>3 SSD · Configure / Optimize<br>4 Network · Observe / Diagnose / Verify<br>5 OS · Diagnose / Configure | 1 · Systems sources (CR1 / DeepSpeed ZeRO-Infinity @ `5f266e26d216a705d9c64cac88fb813ce ...)<br>1 · Systems sources (CR5 / Ascend MindSpeed adaptive memory — `core_r0.8.0`, page ...)<br>1 · Systems sources (ZeRO-Offload — [2101.06840v1](https://arxiv.org/abs/2101.06840v1))<br>2 · Methodology and corpus references (CR6 / Stas Bekman ML Engineering Open Book @ ...) | candidate · not_run · 8 readset(s) | no-eval |
+| [video-diffusion-optimization](../src/inferrsi/data/skill_library/methods/video-diffusion-optimization/SKILL.md) | common | Run and verify goal-driven video diffusion optimization, backend-agnostic. Use when the user asks for latency, RTF ... | — | — | candidate · not_run · 0 readset(s) | no-SearchSpace-layer, no-Reference-Matrix-row, no-eval |
 | [weight-loading-optimization](../src/inferrsi/data/skill_library/methods/weight-loading-optimization/SKILL.md) | common | Optimize the serving-level weight load path from storage to device: judge the load path on four dimensions (source ... | 1 Accelerator † guidance: Flare preparation and complete-session source contracts<br>2 RAM/Host † guidance: Flare preparation and complete-session source contracts<br>3 SSD · Observe / Profile / Diagnose / Optimize / Verify † guidance: Flare preparation and complete-session source contracts<br>4 Network · Configure / Optimize / Verify | 1 · Systems sources (Ascend/MindIE-SD @ 8481d39)<br>1 · Systems sources (NVIDIA/TensorRT-LLM @ f33e0e5fd)<br>1 · Systems sources (ascend-ai-coding/awesome-ascend-skills @ 75ec89c)<br>1 · Systems sources (foundation-model-stack/fastsafetensors @ 219e256)<br>1 · Systems sources (ggml-org/llama.cpp @ `3e390af18de1131dda27913c00511725b4274c8a` (MIT ...)<br>1 · Systems sources (mindie-agent/mindie-agent @ 6a81b41) | candidate · not_run · 3 readset(s) | no-eval |
 
 ## Registered: Workflows (6)
@@ -203,7 +204,7 @@ an entrypoint routes to procedures below it rather than adding one.
 
 ## Integrity checks
 
-- Registered ids resolve to an existing `SKILL.md`: 75 of 75.
+- Registered ids resolve to an existing `SKILL.md`: 76 of 76.
 - Duplicate ids or paths: none; `skill_catalog` rejects them before this view is built.
 - Skill links in the two matrices that do not resolve: 0.
 - Registered skills without a `metadata.json` sidecar: 5.
@@ -212,10 +213,10 @@ an entrypoint routes to procedures below it rather than adding one.
 
 | Gap | Skills |
 |---|---|
-| `no-SearchSpace-layer` | 14: ascend-video-diffusion-optimization, audit-fixed-workload-claim, audit-recurrent-kv-finalization, cite-check-downstream-pr, competitor-scan, draft-acceptance-issue, dwarfstar, husky, inference-benchmark-design, lily, npu-skill-factory, repository-evolution-analysis, skill-evolution-playbook, splash |
-| `no-Reference-Matrix-row` | 7: ascend-video-diffusion-optimization, audit-fixed-workload-claim, cite-check-downstream-pr, claim-contract, competitor-scan, draft-acceptance-issue, rsi-evidence |
+| `no-SearchSpace-layer` | 15: ascend-video-diffusion-optimization, audit-fixed-workload-claim, audit-recurrent-kv-finalization, cite-check-downstream-pr, competitor-scan, draft-acceptance-issue, dwarfstar, husky, inference-benchmark-design, lily, npu-skill-factory, repository-evolution-analysis, skill-evolution-playbook, splash, video-diffusion-optimization |
+| `no-Reference-Matrix-row` | 8: ascend-video-diffusion-optimization, audit-fixed-workload-claim, cite-check-downstream-pr, claim-contract, competitor-scan, draft-acceptance-issue, rsi-evidence, video-diffusion-optimization |
 | `no-sidecar` | 5: cite-check-downstream-pr, claim-contract, competitor-scan, draft-acceptance-issue, rsi-evidence |
-| `no-eval` | 73: as listed in the Gaps column above |
+| `no-eval` | 74: as listed in the Gaps column above |
 
 These are inventory gaps, not defects. A workflow skill may legitimately
 have no hardware resource layer; a candidate may legitimately be untested.
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md b/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md
index a86cb875e..cca085118 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md
@@ -1,6 +1,6 @@
 # InferRSI skill discovery index
 
-Generated abstracts for all 75 registered skills in `data/skill_library/`.
+Generated abstracts for all 76 registered skills in `data/skill_library/`.
 Their complete procedures, references and cases ship in the same package.
 `skill-index.json` maps stable skill IDs to categorized directories. The
 reference and searchspace matrices
@@ -15,7 +15,7 @@ These are knowledge abstracts (`--kind knowledge`), with namespaced package
 IDs distinct from explicitly selected `checkout_ref` skills. Ascend/CUDA
 procedures use their corresponding backend; shared methods use `common`.
 
-Source snapshot: [e71d0631a1c0854c9616d8ef5e174d3a1e14af4b](https://github.com/InferMatrixLab/InferRSI/tree/e71d0631a1c0854c9616d8ef5e174d3a1e14af4b/src/inferrsi/data/skill_library).
+Source snapshot: [f0e87c48809601d38035960d26737e0698489165](https://github.com/InferMatrixLab/InferRSI/tree/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library).
 
 ```bash
 inferrsi knowledge search 'profiling' --repo-type inferrsi --limit 50
@@ -29,7 +29,7 @@ contain the current input paths and bytes (Git checkout filters are respected).
 
 ```bash
 python tools/build_skill_index.py --source-revision <committed-source-revision>
-python tools/build_skill_index.py --source-revision e71d0631a1c0854c9616d8ef5e174d3a1e14af4b --check
+python tools/build_skill_index.py --source-revision f0e87c48809601d38035960d26737e0698489165 --check
 ```
 
 `--check` detects missing, stale and unexpected generated records without writing.
@@ -110,5 +110,6 @@ References and cases ship with their owning skill, not as duplicate knowledge ab
 | [torchnpu-pinned-host-memory-lifecycle](ascend/skills/torchnpu-pinned-host-memory-lifecycle.json) | ascend | candidate |
 | [training-input-pipeline](common/skills/training-input-pipeline.json) | common | candidate |
 | [training-resource-budget](common/skills/training-resource-budget.json) | common | candidate |
+| [video-diffusion-optimization](common/skills/video-diffusion-optimization.json) | common | candidate |
 | [vllm-metal](common/skills/vllm-metal.json) | common | candidate |
 | [weight-loading-optimization](common/skills/weight-loading-optimization.json) | common | candidate |
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json
index 95b194dca..06408d8f1 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json
@@ -21,8 +21,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/e71d0631a1c0854c9616d8ef5e174d3a1e14af4b/src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/SKILL.md",
-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/SKILL.md",
+      "commit": "f0e87c48809601d38035960d26737e0698489165",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/metadata.json",
@@ -41,7 +41,7 @@
     "src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/SKILL.md": "d494fc7e539cbb7388189bd7b3f04bb5c4983fdd7a82484348aad1cee7f741f2",
     "src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/metadata.json": "71c68431663ed2336cccc985a354adab6b13b4cfd6123a18a5d8d53c28268509",
     "src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/references/source-notes.md": "6ffbfb68cc7e04923b4fbca2a73a7555b7c3b45a6f40819bb5f3213ef05cf88d",
-    "src/inferrsi/data/skill_library/skill-index.json": "eaf446cb37baa90d40166119ca17cc0a434dbe3f77611423f648b0f225903f7c"
+    "src/inferrsi/data/skill_library/skill-index.json": "531190c468b6fb385b9b4aa71e666e8dd20d92aa5adc54bf4040f2096e3dd190"
   },
   "skill_metadata": {
     "name": "ascend-aclgraph-capture-replay",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json
index 6b734c60f..ae8fb128c 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/e71d0631a1c0854c9616d8ef5e174d3a1e14af4b/src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/SKILL.md",
-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/SKILL.md",
+      "commit": "f0e87c48809601d38035960d26737e0698489165",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/metadata.json",
@@ -41,7 +41,7 @@
   "source_files": {
     "src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/SKILL.md": "03829039860ece35519f2e4c339a48b5014ec25e07a2c150a3efb6a3a4e35b4a",
     "src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/metadata.json": "80d80c15514919826fa72d6f6cf26b76db8accd85d21187fc239232ca454e7bf",
-    "src/inferrsi/data/skill_library/skill-index.json": "eaf446cb37baa90d40166119ca17cc0a434dbe3f77611423f648b0f225903f7c"
+    "src/inferrsi/data/skill_library/skill-index.json": "531190c468b6fb385b9b4aa71e666e8dd20d92aa5adc54bf4040f2096e3dd190"
   },
   "skill_metadata": {
     "name": "ascend-device-health",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json
index 1f88d859a..5675bdfa3 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/e71d0631a1c0854c9616d8ef5e174d3a1e14af4b/src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/SKILL.md",
-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/SKILL.md",
+      "commit": "f0e87c48809601d38035960d26737e0698489165",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/metadata.json",
@@ -44,7 +44,7 @@
     "src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/SKILL.md": "4ce9dcadd1ae3c7a8cc633336760d0a3c382f354f1b7028e3a10d28fa0d0c9fa",
     "src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/metadata.json": "b6cb25879b1bca5f5af08b48776f2e664cf5dcd11a0efb1c4f56879e2afa9006",
     "src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/references/awesome-ascend-communication-tests.md": "0cb27a3d24409171bb414d7ebf0c49ad62be5f46482f29624695496ba9eb3e63",
-    "src/inferrsi/data/skill_library/skill-index.json": "eaf446cb37baa90d40166119ca17cc0a434dbe3f77611423f648b0f225903f7c"
+    "src/inferrsi/data/skill_library/skill-index.json": "531190c468b6fb385b9b4aa71e666e8dd20d92aa5adc54bf4040f2096e3dd190"
   },
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json
index 9478e673a..b80ebae89 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/e71d0631a1c0854c9616d8ef5e174d3a1e14af4b/src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/SKILL.md",
-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/SKILL.md",
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@@ -40,7 +40,7 @@
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-    "src/inferrsi/data/skill_library/skill-index.json": "eaf446cb37baa90d40166119ca17cc0a434dbe3f77611423f648b0f225903f7c"
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   },
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json
index 9a6f2be35..aa32621fb 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json
@@ -22,8 +22,8 @@
   "sources": [
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       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/e71d0631a1c0854c9616d8ef5e174d3a1e14af4b/src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/SKILL.md",
-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/SKILL.md",
+      "commit": "f0e87c48809601d38035960d26737e0698489165",
       "paths": [
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         "src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/metadata.json",
@@ -40,7 +40,7 @@
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     "src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/metadata.json": "be681a3206e5e183b4c9670c9d7784bcffce18c891449e5b15f94ca5f1324b9a",
-    "src/inferrsi/data/skill_library/skill-index.json": "eaf446cb37baa90d40166119ca17cc0a434dbe3f77611423f648b0f225903f7c"
+    "src/inferrsi/data/skill_library/skill-index.json": "531190c468b6fb385b9b4aa71e666e8dd20d92aa5adc54bf4040f2096e3dd190"
   },
   "skill_metadata": {
     "name": "ascend-model-adaptation",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json
index 0a16ef01b..ef4cec2a7 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/e71d0631a1c0854c9616d8ef5e174d3a1e14af4b/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/SKILL.md",
-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/SKILL.md",
+      "commit": "f0e87c48809601d38035960d26737e0698489165",
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@@ -41,7 +41,7 @@
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     "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/metadata.json": "efd37bb23acb500dad4ec8ebe7ddfe5c3f196374052825f923ac85da8445f06b",
-    "src/inferrsi/data/skill_library/skill-index.json": "eaf446cb37baa90d40166119ca17cc0a434dbe3f77611423f648b0f225903f7c"
+    "src/inferrsi/data/skill_library/skill-index.json": "531190c468b6fb385b9b4aa71e666e8dd20d92aa5adc54bf4040f2096e3dd190"
   },
   "skill_metadata": {
     "name": "ascend-operator-profiling",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json
index 265f04a1c..f0b709b41 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/e71d0631a1c0854c9616d8ef5e174d3a1e14af4b/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/SKILL.md",
-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/SKILL.md",
+      "commit": "f0e87c48809601d38035960d26737e0698489165",
       "paths": [
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@@ -42,7 +42,7 @@
   "source_files": {
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     "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/metadata.json": "04d2002fc8a0a7becf86b0b73daaf2da8716ab466d7f988da43d41a10f26680e",
-    "src/inferrsi/data/skill_library/skill-index.json": "eaf446cb37baa90d40166119ca17cc0a434dbe3f77611423f648b0f225903f7c"
+    "src/inferrsi/data/skill_library/skill-index.json": "531190c468b6fb385b9b4aa71e666e8dd20d92aa5adc54bf4040f2096e3dd190"
   },
   "skill_metadata": {
     "name": "ascend-operator-tuning",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json
index 0e7992bfc..5e2f37d70 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/e71d0631a1c0854c9616d8ef5e174d3a1e14af4b/src/inferrsi/data/skill_library/hardware/ascend/ascend-optimization-casebook/SKILL.md",
-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/hardware/ascend/ascend-optimization-casebook/SKILL.md",
+      "commit": "f0e87c48809601d38035960d26737e0698489165",
       "paths": [
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@@ -40,7 +40,7 @@
   "source_files": {
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-    "src/inferrsi/data/skill_library/skill-index.json": "eaf446cb37baa90d40166119ca17cc0a434dbe3f77611423f648b0f225903f7c"
+    "src/inferrsi/data/skill_library/skill-index.json": "531190c468b6fb385b9b4aa71e666e8dd20d92aa5adc54bf4040f2096e3dd190"
   },
   "skill_metadata": {
     "name": "ascend-optimization-casebook",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-performance-analysis.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-performance-analysis.json
index 772272880..c4f8fb487 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-performance-analysis.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-performance-analysis.json
@@ -22,8 +22,8 @@
   "sources": [
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-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/e71d0631a1c0854c9616d8ef5e174d3a1e14af4b/src/inferrsi/data/skill_library/hardware/ascend/ascend-performance-analysis/SKILL.md",
-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/hardware/ascend/ascend-performance-analysis/SKILL.md",
+      "commit": "f0e87c48809601d38035960d26737e0698489165",
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@@ -44,7 +44,7 @@
     "src/inferrsi/data/skill_library/hardware/ascend/ascend-performance-analysis/metadata.json": "9e705625c8308013c287576b0247da6f6116d817a4a535cbecff80abd6ea35ee",
     "src/inferrsi/data/skill_library/hardware/ascend/ascend-performance-analysis/references/cannbot-CANN-2.0-LICENSE.md": "89b1c114df62cfd183004f38d18d07f186436c3b37203dd69c3e84becf9d2282",
     "src/inferrsi/data/skill_library/hardware/ascend/ascend-performance-analysis/references/cannbot-stage-evidence.md": "f56e4125325c9c1b9235a1d64fd732861c7686444492422daff44ba8dd648be4",
-    "src/inferrsi/data/skill_library/skill-index.json": "eaf446cb37baa90d40166119ca17cc0a434dbe3f77611423f648b0f225903f7c"
+    "src/inferrsi/data/skill_library/skill-index.json": "531190c468b6fb385b9b4aa71e666e8dd20d92aa5adc54bf4040f2096e3dd190"
   },
   "skill_metadata": {
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-video-diffusion-optimization.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-video-diffusion-optimization.json
index 521960f1a..0768065f0 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-video-diffusion-optimization.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-video-diffusion-optimization.json
@@ -8,7 +8,7 @@
   "component": "skills",
   "scenario": "skills.discovery",
   "status": "imported",
-  "summary": "Run and verify goal-driven Ascend video diffusion optimization. Use when the user asks for latency, RTF, throughput, or HBM targets across VLM, DiT, MoE, attention, or VAE. Not for text-only LLMs.",
+  "summary": "Run and verify goal-driven Ascend video diffusion optimization. Specializes the backend-agnostic video-diffusion-optimization skeleton with Ascend NPU operator, layout and profiler references. Use when the user asks for latency, RTF, throughput, or HBM targets across VLM, DiT, MoE, attention, or VAE on Ascend NPU. Not for text-only LLMs.",
   "tags": [
     "ascend",
     "npu",
@@ -26,17 +26,15 @@
   "sources": [
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-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/e71d0631a1c0854c9616d8ef5e174d3a1e14af4b/src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/SKILL.md",
-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/SKILL.md",
+      "commit": "f0e87c48809601d38035960d26737e0698489165",
       "paths": [
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-        "src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/assets/campaign.template.json",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/metadata.json",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/references/field-notes-video-diffusion.md",
-        "src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/scripts/evaluate_target.py",
         "src/inferrsi/data/skill_library/skill-index.json"
       ],
-      "content_sha256": "bb08bb6de8b2c818dbcbcca9da649da5d4ae99b6771aaad6eba32d5f4b25f935"
+      "content_sha256": "53c21e64f0dd47f9510faef1f2c01e1283899787ba7ebfe70cdabd8e57a76f00"
     }
   ],
   "index_type": "packaged-skill",
@@ -45,16 +43,14 @@
   },
   "checkout_ref": "checkout:ascend-video-diffusion-optimization",
   "source_files": {
-    "src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/SKILL.md": "bb08bb6de8b2c818dbcbcca9da649da5d4ae99b6771aaad6eba32d5f4b25f935",
-    "src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/assets/campaign.template.json": "1a37f1d136612143ddab8f0cbbf424c80433b4da5312edb18d07c0b9d87ef657",
-    "src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/metadata.json": "8622da20f59c40d798e57ff9e8c8dff69137854d79dd6ed883c1a5558d3d4f92",
+    "src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/SKILL.md": "53c21e64f0dd47f9510faef1f2c01e1283899787ba7ebfe70cdabd8e57a76f00",
+    "src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/metadata.json": "8c2b364298330751fd1252516159b16c27e90354e2a724782d2851e68e43cdb3",
     "src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/references/field-notes-video-diffusion.md": "dadac7b23462fdc325218c72ddf8a2ac553151761a5d3e45b854b53d2c8c6908",
-    "src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/scripts/evaluate_target.py": "9e84df051e03d567746fd73ae7243efb2f3c5ec806fef824d3c4d42a8eb9704c",
-    "src/inferrsi/data/skill_library/skill-index.json": "eaf446cb37baa90d40166119ca17cc0a434dbe3f77611423f648b0f225903f7c"
+    "src/inferrsi/data/skill_library/skill-index.json": "531190c468b6fb385b9b4aa71e666e8dd20d92aa5adc54bf4040f2096e3dd190"
   },
   "skill_metadata": {
     "name": "ascend-video-diffusion-optimization",
-    "description": "Run and verify goal-driven Ascend video diffusion optimization. Use when the user asks for latency, RTF, throughput, or HBM targets across VLM, DiT, MoE, attention, or VAE. Not for text-only LLMs.",
+    "description": "Run and verify goal-driven Ascend video diffusion optimization. Specializes the backend-agnostic video-diffusion-optimization skeleton with Ascend NPU operator, layout and profiler references. Use when the user asks for latency, RTF, throughput, or HBM targets across VLM, DiT, MoE, attention, or VAE on Ascend NPU. Not for text-only LLMs.",
     "schema_version": 1,
     "profile": "local-skill-v1",
     "kind": "skill",
@@ -81,10 +77,11 @@
     },
     "applicability": {
       "scope": "Ascend NPU video diffusion inference and serving optimization",
-      "hardware": "Ascend NPU; procedures are hardware-agnostic apart from layout and profiler references",
+      "hardware": "Ascend NPU; the measure-change-verify workflow skeleton is backend-agnostic and lives in methods/video-diffusion-optimization, while the operator, layout and profiler references here are Ascend-specific",
       "prerequisites": "A reproducible benchmark, a frozen quality check, and numeric gates defined in the governing acceptance issue"
     },
     "limitations": [
+      "Ascend specialization of the backend-agnostic methods/video-diffusion-optimization skeleton; every operator, layout and profiler reference (TransData, FRACTAL_NZ, CANN) is Ascend-specific and must be re-derived per backend.",
       "Candidate workflow guidance; not independently validated beyond the field notes.",
       "Field notes are non-reproducible as published and must not be cited as evidence.",
       "Model identifiers, campaign revisions, and numeric gates are intentionally excluded and remain issue-scoped.",
@@ -93,11 +90,16 @@
     "provenance_readsets": [
       "references/field-notes-video-diffusion.md"
     ],
+    "references": [
+      "../../../methods/video-diffusion-optimization/SKILL.md",
+      "../../../methods/video-diffusion-optimization/scripts/evaluate_target.py",
+      "../../../methods/video-diffusion-optimization/assets/campaign.template.json"
+    ],
     "consumption_mode": "packaged"
   },
   "applicability": {
     "scope": "Ascend NPU video diffusion inference and serving optimization",
-    "hardware": "Ascend NPU; procedures are hardware-agnostic apart from layout and profiler references",
+    "hardware": "Ascend NPU; the measure-change-verify workflow skeleton is backend-agnostic and lives in methods/video-diffusion-optimization, while the operator, layout and profiler references here are Ascend-specific",
     "prerequisites": "A reproducible benchmark, a frozen quality check, and numeric gates defined in the governing acceptance issue"
   },
   "recommendations": [
@@ -109,6 +111,7 @@
     "The imported status describes this index, not the original skill; its declared status is candidate.",
     "Reading or indexing does not authorize execution, validate efficacy, promote a candidate or grant a license.",
     "The backend categorizes the procedure's hardware dependency; it does not certify compatibility, and skills.discovery is a discovery scenario.",
+    "Ascend specialization of the backend-agnostic methods/video-diffusion-optimization skeleton; every operator, layout and profiler reference (TransData, FRACTAL_NZ, CANN) is Ascend-specific and must be re-derived per backend.",
     "Candidate workflow guidance; not independently validated beyond the field notes.",
     "Field notes are non-reproducible as published and must not be cited as evidence.",
     "Model identifiers, campaign revisions, and numeric gates are intentionally excluded and remain issue-scoped.",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascendc-tiling-design.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascendc-tiling-design.json
index 60a79cedd..4c9592e5e 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascendc-tiling-design.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascendc-tiling-design.json
@@ -24,8 +24,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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index 294fb273c..9da2da554 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/cann-attribution-overlap.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/cann-attribution-overlap.json
@@ -24,8 +24,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-device-memory-lifecycle.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-device-memory-lifecycle.json
index 0202d0f52..5055e37b0 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-device-memory-lifecycle.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-device-memory-lifecycle.json
@@ -22,8 +22,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-pinned-host-memory-lifecycle.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-pinned-host-memory-lifecycle.json
index 22da6f075..1eb10412f 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-pinned-host-memory-lifecycle.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-pinned-host-memory-lifecycle.json
@@ -22,8 +22,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/hardware/ascend/torchnpu-pinned-host-memory-lifecycle/SKILL.md",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-serving-preemption.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-serving-preemption.json
index 485e822f4..b52961fd6 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-serving-preemption.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-serving-preemption.json
@@ -16,8 +16,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-split-backward-schedule.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-split-backward-schedule.json
index 8962eac2e..c63ae706c 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-split-backward-schedule.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-split-backward-schedule.json
@@ -16,8 +16,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-fixed-workload-claim.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-fixed-workload-claim.json
index 67e5db789..510095f32 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-fixed-workload-claim.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-fixed-workload-claim.json
@@ -20,8 +20,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-h3-metal-fasth3-semantics.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-h3-metal-fasth3-semantics.json
index 90390e5c7..5b46c6499 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-h3-metal-fasth3-semantics.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-h3-metal-fasth3-semantics.json
@@ -29,8 +29,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-h3-runtime-residency.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-h3-runtime-residency.json
index 57f57d712..1715a9e00 100644
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+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-h3-runtime-residency.json
@@ -30,8 +30,8 @@
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index 39b079cf3..0c9b17bac 100644
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index 7dbaaa68f..a10801ef2 100644
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index f17025f80..302943145 100644
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index 7f7d2b747..3f31fa901 100644
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index fdb23969f..9feeff19a 100644
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index a622fb907..d0b192f02 100644
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index 1776ce817..59201a0d5 100644
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index 5065534b3..bb7e49706 100644
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index b3fd79c3c..e59e76184 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cgroup-resource-controls.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cgroup-resource-controls.json
@@ -25,8 +25,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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@@ -43,7 +43,7 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/checkpoint-recovery-consistency.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/checkpoint-recovery-consistency.json
index d1d0d4923..a5609d65c 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/checkpoint-recovery-consistency.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/checkpoint-recovery-consistency.json
@@ -22,8 +22,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/choose-parallel-training-plan.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/choose-parallel-training-plan.json
index e5993e752..d058781f8 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/choose-parallel-training-plan.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/choose-parallel-training-plan.json
@@ -16,8 +16,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cite-check-downstream-pr.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cite-check-downstream-pr.json
index f78d3e429..80359ecd6 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cite-check-downstream-pr.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cite-check-downstream-pr.json
@@ -16,8 +16,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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@@ -31,7 +31,7 @@
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index 3d06e1e0c..84e327743 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/claim-contract.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/claim-contract.json
@@ -16,8 +16,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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@@ -31,7 +31,7 @@
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index c4fc635b4..0ec4ef6bd 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/comfy-ui.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/comfy-ui.json
@@ -22,8 +22,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/competitor-scan.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/competitor-scan.json
index f49897ad9..d9b673211 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/competitor-scan.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/competitor-scan.json
@@ -16,8 +16,8 @@
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@@ -31,7 +31,7 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dcp-async-save-performance.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dcp-async-save-performance.json
index e8742c0b8..512b113a9 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dcp-async-save-performance.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dcp-async-save-performance.json
@@ -23,8 +23,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dense-performance-evidence.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dense-performance-evidence.json
index 4bcdec4e7..97583d312 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dense-performance-evidence.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dense-performance-evidence.json
@@ -21,8 +21,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/diagnose-vllm-admission-pressure.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/diagnose-vllm-admission-pressure.json
index 1330dca6a..b65113889 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/diagnose-vllm-admission-pressure.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/diagnose-vllm-admission-pressure.json
@@ -21,8 +21,8 @@
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@@ -67,7 +67,7 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/diffusers-invocation-state.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/diffusers-invocation-state.json
index 98ade737b..7ccdbbacd 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/diffusers-invocation-state.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/diffusers-invocation-state.json
@@ -22,8 +22,8 @@
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@@ -46,7 +46,7 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/draft-acceptance-issue.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/draft-acceptance-issue.json
index c8b5d4827..ec8abb140 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/draft-acceptance-issue.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/draft-acceptance-issue.json
@@ -16,8 +16,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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index f9e66bef7..5a62d1a0a 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dwarfstar.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dwarfstar.json
@@ -25,8 +25,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/evaluate-elastic-serving-placement.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/evaluate-elastic-serving-placement.json
index 19977f5ec..33271707d 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/evaluate-elastic-serving-placement.json
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@@ -16,8 +16,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/generation-cache-lifecycle.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/generation-cache-lifecycle.json
index 6e0993f7b..46f700c82 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/generation-cache-lifecycle.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/generation-cache-lifecycle.json
@@ -22,8 +22,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-memory-management.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-memory-management.json
index 80af8ed97..f6dabb8b4 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-memory-management.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-memory-management.json
@@ -27,8 +27,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-overhead-optimization.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-overhead-optimization.json
index bf707ea0b..edff7fdbf 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-overhead-optimization.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-overhead-optimization.json
@@ -22,8 +22,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/husky.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/husky.json
index 13508a780..0f838c37b 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/husky.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/husky.json
@@ -21,8 +21,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/inference-benchmark-design.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/inference-benchmark-design.json
index c84f5b1ed..0dbf90939 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/inference-benchmark-design.json
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@@ -30,8 +30,8 @@
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index 11220a781..dbfc09063 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/inference-optimization-casebook.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/inference-optimization-casebook.json
@@ -21,8 +21,8 @@
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index 4f7807306..3d74b0f6a 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/kernel-writing-guide.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/kernel-writing-guide.json
@@ -32,8 +32,8 @@
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index 04e5c7a0c..cb7594da1 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/kv-tier-management.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/kv-tier-management.json
@@ -24,8 +24,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/lazy-evaluation-stream-lifetimes.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/lazy-evaluation-stream-lifetimes.json
index 11c87a214..8d45f4516 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/lazy-evaluation-stream-lifetimes.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/lazy-evaluation-stream-lifetimes.json
@@ -22,8 +22,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/lily.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/lily.json
index d09aed26e..8c926eef2 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/lily.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/lily.json
@@ -25,8 +25,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/local-dream.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/local-dream.json
index 63cf6def8..d4c4562c3 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/local-dream.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/local-dream.json
@@ -29,8 +29,8 @@
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index b56895620..38bfabb53 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mistral-rs.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mistral-rs.json
@@ -26,8 +26,8 @@
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index 509932cb0..b74f099b0 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mlc-llm.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mlc-llm.json
@@ -27,8 +27,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mlx-swift-lm.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mlx-swift-lm.json
index 78539ee32..a2d95f3ae 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mlx-swift-lm.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mlx-swift-lm.json
@@ -27,8 +27,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/npu-skill-factory.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/npu-skill-factory.json
index de598fa45..0fb43199a 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/npu-skill-factory.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/npu-skill-factory.json
@@ -22,8 +22,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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@@ -54,7 +54,7 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/optimization-search-policy.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/optimization-search-policy.json
index 7fa7e7784..061176236 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/optimization-search-policy.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/optimization-search-policy.json
@@ -21,8 +21,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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@@ -51,7 +51,7 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/os-process-placement.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/os-process-placement.json
index bdb804243..bdcfd72d5 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/os-process-placement.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/os-process-placement.json
@@ -24,8 +24,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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@@ -44,7 +44,7 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/performance-ceiling-analysis.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/performance-ceiling-analysis.json
index a86d59ffd..f32c55de8 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/performance-ceiling-analysis.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/performance-ceiling-analysis.json
@@ -22,8 +22,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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@@ -78,7 +78,7 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/plan-activation-residency.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/plan-activation-residency.json
index 0db4b101a..7ad796d4a 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/plan-activation-residency.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/plan-activation-residency.json
@@ -16,8 +16,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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@@ -36,7 +36,7 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/project-maya.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/project-maya.json
index 86a9b112d..e33329c0a 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/project-maya.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/project-maya.json
@@ -25,8 +25,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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@@ -83,7 +83,7 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/repository-evolution-analysis.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/repository-evolution-analysis.json
index 7ca9ba89f..952a60267 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/repository-evolution-analysis.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/repository-evolution-analysis.json
@@ -21,8 +21,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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@@ -41,7 +41,7 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/rsi-evidence.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/rsi-evidence.json
index 018f1c00a..4a81c9db9 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/rsi-evidence.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/rsi-evidence.json
@@ -16,8 +16,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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@@ -38,7 +38,7 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/skill-evolution-playbook.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/skill-evolution-playbook.json
index e70e35336..f695a765e 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/skill-evolution-playbook.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/skill-evolution-playbook.json
@@ -21,8 +21,8 @@
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-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
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@@ -39,7 +39,7 @@
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     "src/inferrsi/data/skill_library/methods/skill-evolution-playbook/metadata.json": "92b36338b9257e2e41b95e4370694d7de52ed84bc7971056b3bfced07b0993d8",
-    "src/inferrsi/data/skill_library/skill-index.json": "eaf446cb37baa90d40166119ca17cc0a434dbe3f77611423f648b0f225903f7c"
+    "src/inferrsi/data/skill_library/skill-index.json": "531190c468b6fb385b9b4aa71e666e8dd20d92aa5adc54bf4040f2096e3dd190"
   },
   "skill_metadata": {
     "name": "skill-evolution-playbook",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/splash.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/splash.json
index 7d7a362d2..48b890d85 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/splash.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/splash.json
@@ -25,8 +25,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/e71d0631a1c0854c9616d8ef5e174d3a1e14af4b/src/inferrsi/data/skill_library/repositories/splash/SKILL.md",
-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/repositories/splash/SKILL.md",
+      "commit": "f0e87c48809601d38035960d26737e0698489165",
       "paths": [
         "src/inferrsi/data/skill_library/repositories/splash/LICENSE",
         "src/inferrsi/data/skill_library/repositories/splash/SKILL.md",
@@ -77,7 +77,7 @@
     "src/inferrsi/data/skill_library/repositories/splash/sub-skills/serving-cache/SKILL.md": "c16f911498e116ff9b31b5a6f0ddd3ae6517b51c0e9d079c337f36a5bcac1df8",
     "src/inferrsi/data/skill_library/repositories/splash/sub-skills/serving-cache/references/state-and-api.md": "592603177473ac8e024b7dc19a3d3faedd7c1e0312137eab8bf9a62d2f567be6",
     "src/inferrsi/data/skill_library/repositories/splash/sub-skills/serving-cache/references/troubleshooting.md": "4fda461042a3de43c109d7a3cec67542c7d61fe68412bf91606220f2e13e576e",
-    "src/inferrsi/data/skill_library/skill-index.json": "eaf446cb37baa90d40166119ca17cc0a434dbe3f77611423f648b0f225903f7c"
+    "src/inferrsi/data/skill_library/skill-index.json": "531190c468b6fb385b9b4aa71e666e8dd20d92aa5adc54bf4040f2096e3dd190"
   },
   "skill_metadata": {
     "name": "splash",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/storage-io-measurement.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/storage-io-measurement.json
index 840cb15ec..d7f259706 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/storage-io-measurement.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/storage-io-measurement.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/e71d0631a1c0854c9616d8ef5e174d3a1e14af4b/src/inferrsi/data/skill_library/hardware/host/storage-io-measurement/SKILL.md",
-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/hardware/host/storage-io-measurement/SKILL.md",
+      "commit": "f0e87c48809601d38035960d26737e0698489165",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/host/storage-io-measurement/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/host/storage-io-measurement/metadata.json",
@@ -42,7 +42,7 @@
   "source_files": {
     "src/inferrsi/data/skill_library/hardware/host/storage-io-measurement/SKILL.md": "63b883c10a8d3e7d918abfc7175b72e2b401ff1e02697f94b8382ec1c8f369b7",
     "src/inferrsi/data/skill_library/hardware/host/storage-io-measurement/metadata.json": "0a41c7b00978332b54ee1e4a7c1ade88ecde3e961128f24d1b4f7708caff5ff5",
-    "src/inferrsi/data/skill_library/skill-index.json": "eaf446cb37baa90d40166119ca17cc0a434dbe3f77611423f648b0f225903f7c"
+    "src/inferrsi/data/skill_library/skill-index.json": "531190c468b6fb385b9b4aa71e666e8dd20d92aa5adc54bf4040f2096e3dd190"
   },
   "skill_metadata": {
     "name": "storage-io-measurement",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-input-pipeline.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-input-pipeline.json
index b2a6a5d82..af1638616 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-input-pipeline.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-input-pipeline.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/e71d0631a1c0854c9616d8ef5e174d3a1e14af4b/src/inferrsi/data/skill_library/methods/training-input-pipeline/SKILL.md",
-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/methods/training-input-pipeline/SKILL.md",
+      "commit": "f0e87c48809601d38035960d26737e0698489165",
       "paths": [
         "src/inferrsi/data/skill_library/methods/training-input-pipeline/SKILL.md",
         "src/inferrsi/data/skill_library/methods/training-input-pipeline/metadata.json",
@@ -43,7 +43,7 @@
     "src/inferrsi/data/skill_library/methods/training-input-pipeline/SKILL.md": "64bd2c6b795d966045d1d3cca55976d3d49b08b06df7c7e06a70c2824cf55b7e",
     "src/inferrsi/data/skill_library/methods/training-input-pipeline/metadata.json": "80659099fce6a6ec05e9084b75452c877a5812e30f60a78f31ef8c7efcdc1bac",
     "src/inferrsi/data/skill_library/methods/training-input-pipeline/references/sources.md": "60e0f3e88655d8e1d5eb4797f39ca4370deda01614f265b8d2ea4559d8ac020f",
-    "src/inferrsi/data/skill_library/skill-index.json": "eaf446cb37baa90d40166119ca17cc0a434dbe3f77611423f648b0f225903f7c"
+    "src/inferrsi/data/skill_library/skill-index.json": "531190c468b6fb385b9b4aa71e666e8dd20d92aa5adc54bf4040f2096e3dd190"
   },
   "skill_metadata": {
     "name": "training-input-pipeline",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-resource-budget.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-resource-budget.json
index d3695ceef..f2f896072 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-resource-budget.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-resource-budget.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/e71d0631a1c0854c9616d8ef5e174d3a1e14af4b/src/inferrsi/data/skill_library/methods/training-resource-budget/SKILL.md",
-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/methods/training-resource-budget/SKILL.md",
+      "commit": "f0e87c48809601d38035960d26737e0698489165",
       "paths": [
         "src/inferrsi/data/skill_library/methods/training-resource-budget/SKILL.md",
         "src/inferrsi/data/skill_library/methods/training-resource-budget/metadata.json",
@@ -57,7 +57,7 @@
     "src/inferrsi/data/skill_library/methods/training-resource-budget/references/papers-20261015/references/source-readset.md": "2a5c166767f56fa47e7eba7386f1f36da8cb73702e5b5bbe14d6a456ca9ebfae",
     "src/inferrsi/data/skill_library/methods/training-resource-budget/references/sources.md": "6d248f58af8b350fc66c22898988d6f451ac60d03bcd805cd6e84df5e55174ac",
     "src/inferrsi/data/skill_library/methods/training-resource-budget/references/stas-decision-notes.md": "f1a993e6c4ca9a035a2effcaf5500081f227b0cc56cc885a6b22fda0041fc744",
-    "src/inferrsi/data/skill_library/skill-index.json": "eaf446cb37baa90d40166119ca17cc0a434dbe3f77611423f648b0f225903f7c"
+    "src/inferrsi/data/skill_library/skill-index.json": "531190c468b6fb385b9b4aa71e666e8dd20d92aa5adc54bf4040f2096e3dd190"
   },
   "skill_metadata": {
     "name": "training-resource-budget",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/video-diffusion-optimization.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/video-diffusion-optimization.json
new file mode 100644
index 000000000..3deaf0ad8
--- /dev/null
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/video-diffusion-optimization.json
@@ -0,0 +1,115 @@
+{
+  "schema_version": 1,
+  "id": "inferrsi.common.skills.video_diffusion_optimization",
+  "title": "video-diffusion-optimization",
+  "repo": "inferrsi",
+  "tier": "contribution",
+  "backend": "common",
+  "component": "skills",
+  "scenario": "skills.discovery",
+  "status": "imported",
+  "summary": "Run and verify goal-driven video diffusion optimization, backend-agnostic. Use when the user asks for latency, RTF, throughput, or memory targets across VLM, DiT, MoE, attention, or VAE, on any accelerator. Not for text-only LLMs.",
+  "tags": [
+    "video-diffusion",
+    "dit",
+    "moe",
+    "attention",
+    "vae",
+    "performance",
+    "profiling",
+    "serving",
+    "optimization"
+  ],
+  "origin": [
+    "first-party"
+  ],
+  "sources": [
+    {
+      "type": "git",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/methods/video-diffusion-optimization/SKILL.md",
+      "commit": "f0e87c48809601d38035960d26737e0698489165",
+      "paths": [
+        "src/inferrsi/data/skill_library/methods/video-diffusion-optimization/SKILL.md",
+        "src/inferrsi/data/skill_library/methods/video-diffusion-optimization/assets/campaign.template.json",
+        "src/inferrsi/data/skill_library/methods/video-diffusion-optimization/metadata.json",
+        "src/inferrsi/data/skill_library/methods/video-diffusion-optimization/scripts/evaluate_target.py",
+        "src/inferrsi/data/skill_library/skill-index.json"
+      ],
+      "content_sha256": "fc0e7baf9913ce7448247772a1e224a9cbd827492cf9459b1f17f492b9f67b70"
+    }
+  ],
+  "index_type": "packaged-skill",
+  "skill_documents": {
+    "original": "data/skill_library/methods/video-diffusion-optimization/SKILL.md"
+  },
+  "checkout_ref": "checkout:video-diffusion-optimization",
+  "source_files": {
+    "src/inferrsi/data/skill_library/methods/video-diffusion-optimization/SKILL.md": "fc0e7baf9913ce7448247772a1e224a9cbd827492cf9459b1f17f492b9f67b70",
+    "src/inferrsi/data/skill_library/methods/video-diffusion-optimization/assets/campaign.template.json": "1a37f1d136612143ddab8f0cbbf424c80433b4da5312edb18d07c0b9d87ef657",
+    "src/inferrsi/data/skill_library/methods/video-diffusion-optimization/metadata.json": "b27d69142dfea5dd2820170475c2bf6cced2d5eefd1c43b3413c41849af0fd02",
+    "src/inferrsi/data/skill_library/methods/video-diffusion-optimization/scripts/evaluate_target.py": "9e84df051e03d567746fd73ae7243efb2f3c5ec806fef824d3c4d42a8eb9704c",
+    "src/inferrsi/data/skill_library/skill-index.json": "531190c468b6fb385b9b4aa71e666e8dd20d92aa5adc54bf4040f2096e3dd190"
+  },
+  "skill_metadata": {
+    "name": "video-diffusion-optimization",
+    "description": "Run and verify goal-driven video diffusion optimization, backend-agnostic. Use when the user asks for latency, RTF, throughput, or memory targets across VLM, DiT, MoE, attention, or VAE, on any accelerator. Not for text-only LLMs.",
+    "schema_version": 1,
+    "profile": "local-skill-v1",
+    "kind": "skill",
+    "status": "candidate",
+    "origin": [
+      "first-party"
+    ],
+    "tags": [
+      "video-diffusion",
+      "dit",
+      "moe",
+      "attention",
+      "vae",
+      "performance",
+      "profiling",
+      "serving",
+      "optimization"
+    ],
+    "empirical_validation": "not_run",
+    "verification": {
+      "locally_verified": false,
+      "evidence_level": "guidance",
+      "note": "Procedure is first-hand workflow guidance. The linked field notes are not reproducible as published. No acceptance campaign under this repository's evidence contract backs this skill, and no public performance claim is made."
+    },
+    "applicability": {
+      "scope": "Backend-agnostic video diffusion inference and serving optimization",
+      "hardware": "Any accelerator (Ascend NPU, CUDA GPU, and others); operator names, memory layouts, and profiler references are re-derived per backend",
+      "prerequisites": "A reproducible benchmark, a frozen quality check, and numeric gates defined in the governing acceptance issue"
+    },
+    "limitations": [
+      "Backend-agnostic skeleton only. The first-hand field notes are Ascend-specific and live in the ascend-video-diffusion-optimization skill; every operator, layout and profiler reference (TransData, FRACTAL_NZ, CANN) must be re-derived per backend.",
+      "Candidate workflow guidance; not independently validated.",
+      "Model identifiers, campaign revisions, and numeric gates are intentionally excluded and remain issue-scoped."
+    ],
+    "provenance_readsets": [],
+    "consumption_mode": "packaged"
+  },
+  "applicability": {
+    "scope": "Backend-agnostic video diffusion inference and serving optimization",
+    "hardware": "Any accelerator (Ascend NPU, CUDA GPU, and others); operator names, memory layouts, and profiler references are re-derived per backend",
+    "prerequisites": "A reproducible benchmark, a frozen quality check, and numeric gates defined in the governing acceptance issue"
+  },
+  "recommendations": [
+    "Read the pinned SKILL.md and its prerequisites before choosing this procedure.",
+    "Read the packaged references and owner-local cases alongside the procedure."
+  ],
+  "limitations": [
+    "This generated abstract points to the complete packaged skill; external evidence and upstream repositories remain source links.",
+    "The imported status describes this index, not the original skill; its declared status is candidate.",
+    "Reading or indexing does not authorize execution, validate efficacy, promote a candidate or grant a license.",
+    "The backend categorizes the procedure's hardware dependency; it does not certify compatibility, and skills.discovery is a discovery scenario.",
+    "Backend-agnostic skeleton only. The first-hand field notes are Ascend-specific and live in the ascend-video-diffusion-optimization skill; every operator, layout and profiler reference (TransData, FRACTAL_NZ, CANN) must be re-derived per backend.",
+    "Candidate workflow guidance; not independently validated.",
+    "Model identifiers, campaign revisions, and numeric gates are intentionally excluded and remain issue-scoped."
+  ],
+  "verification": {
+    "locally_verified": false,
+    "evidence_level": "guidance"
+  }
+}
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/vllm-metal.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/vllm-metal.json
index 4e47a8ca5..4ecd1b94b 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/vllm-metal.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/vllm-metal.json
@@ -26,8 +26,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/e71d0631a1c0854c9616d8ef5e174d3a1e14af4b/src/inferrsi/data/skill_library/repositories/vllm-metal/SKILL.md",
-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/repositories/vllm-metal/SKILL.md",
+      "commit": "f0e87c48809601d38035960d26737e0698489165",
       "paths": [
         "src/inferrsi/data/skill_library/repositories/vllm-metal/LICENSE",
         "src/inferrsi/data/skill_library/repositories/vllm-metal/SKILL.md",
@@ -86,7 +86,7 @@
     "src/inferrsi/data/skill_library/repositories/vllm-metal/sub-skills/qualification/references/speculation-and-pipeline.md": "64faced7f31d489e9b0c4b9523a803ff1a76dca0f9315bdc6d0b83935bd338a4",
     "src/inferrsi/data/skill_library/repositories/vllm-metal/sub-skills/qualification/references/troubleshooting.md": "a2e85696120ffc2af4249ac9c1e1b96320e02287e5099577c0474c025ab4f5f6",
     "src/inferrsi/data/skill_library/repositories/vllm-metal/sub-skills/qualification/scripts/summarize_serving_records.py": "78e660a13a6a6941d006cb11fc2f401a34f489e54273860ae6a208dca6a6a3c2",
-    "src/inferrsi/data/skill_library/skill-index.json": "eaf446cb37baa90d40166119ca17cc0a434dbe3f77611423f648b0f225903f7c"
+    "src/inferrsi/data/skill_library/skill-index.json": "531190c468b6fb385b9b4aa71e666e8dd20d92aa5adc54bf4040f2096e3dd190"
   },
   "skill_metadata": {
     "name": "vllm-metal",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json
index d58095a1d..ee2852e5c 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json
@@ -29,8 +29,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/e71d0631a1c0854c9616d8ef5e174d3a1e14af4b/src/inferrsi/data/skill_library/methods/weight-loading-optimization/SKILL.md",
-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/methods/weight-loading-optimization/SKILL.md",
+      "commit": "f0e87c48809601d38035960d26737e0698489165",
       "paths": [
         "src/inferrsi/data/skill_library/methods/weight-loading-optimization/SKILL.md",
         "src/inferrsi/data/skill_library/methods/weight-loading-optimization/metadata.json",
@@ -53,7 +53,7 @@
     "src/inferrsi/data/skill_library/methods/weight-loading-optimization/references/fastsafetensors-transfer-readset.md": "5a39f14b102b0cee304541e011aa31e44e6b13527d1bee9987c3f3b66c064d3d",
     "src/inferrsi/data/skill_library/methods/weight-loading-optimization/references/flare-preparation-boundary.md": "1d7922785a196bdbafdc9791fe79428465a5acc0292ca8f99446f8c764b35454",
     "src/inferrsi/data/skill_library/methods/weight-loading-optimization/references/llama-loading-readset.md": "6c640f28ee3f0253a17b81461c865cb9f947367002cb75bf72550c4572d02e97",
-    "src/inferrsi/data/skill_library/skill-index.json": "eaf446cb37baa90d40166119ca17cc0a434dbe3f77611423f648b0f225903f7c"
+    "src/inferrsi/data/skill_library/skill-index.json": "531190c468b6fb385b9b4aa71e666e8dd20d92aa5adc54bf4040f2096e3dd190"
   },
   "skill_metadata": {
     "name": "weight-loading-optimization",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/audit-afd-p2p-exchanges.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/audit-afd-p2p-exchanges.json
index 4d54e08d8..ae4761011 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/audit-afd-p2p-exchanges.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/audit-afd-p2p-exchanges.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/e71d0631a1c0854c9616d8ef5e174d3a1e14af4b/src/inferrsi/data/skill_library/repositories/afd-plugin/audit-afd-p2p-exchanges/SKILL.md",
-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/repositories/afd-plugin/audit-afd-p2p-exchanges/SKILL.md",
+      "commit": "f0e87c48809601d38035960d26737e0698489165",
       "paths": [
         "src/inferrsi/data/skill_library/repositories/afd-plugin/audit-afd-p2p-exchanges/SKILL.md",
         "src/inferrsi/data/skill_library/repositories/afd-plugin/audit-afd-p2p-exchanges/metadata.json",
@@ -45,7 +45,7 @@
     "src/inferrsi/data/skill_library/repositories/afd-plugin/audit-afd-p2p-exchanges/metadata.json": "4e6100dfb9fc7bc00b19915f4fd38ad509704f2a609c658adf4d632d4e05b6c1",
     "src/inferrsi/data/skill_library/repositories/afd-plugin/audit-afd-p2p-exchanges/references/afd-plugin-LICENSE.md": "0e8566ea362276878e1f38f97da49964dbea301c15d4aa9d727f97a4c39fd943",
     "src/inferrsi/data/skill_library/repositories/afd-plugin/audit-afd-p2p-exchanges/references/source-notes.md": "5073d87450cb60d1b245308dff8807e73749c07de976d50f2fa26694fad81a72",
-    "src/inferrsi/data/skill_library/skill-index.json": "eaf446cb37baa90d40166119ca17cc0a434dbe3f77611423f648b0f225903f7c"
+    "src/inferrsi/data/skill_library/skill-index.json": "531190c468b6fb385b9b4aa71e666e8dd20d92aa5adc54bf4040f2096e3dd190"
   },
   "skill_metadata": {
     "name": "audit-afd-p2p-exchanges",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/audit-flare-session-lifecycle.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/audit-flare-session-lifecycle.json
index 93d0ddb98..e6fb111a8 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/audit-flare-session-lifecycle.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/audit-flare-session-lifecycle.json
@@ -29,8 +29,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/e71d0631a1c0854c9616d8ef5e174d3a1e14af4b/src/inferrsi/data/skill_library/repositories/flare-local-inference/audit-flare-session-lifecycle/SKILL.md",
-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/repositories/flare-local-inference/audit-flare-session-lifecycle/SKILL.md",
+      "commit": "f0e87c48809601d38035960d26737e0698489165",
       "paths": [
         "src/inferrsi/data/skill_library/repositories/flare-local-inference/audit-flare-session-lifecycle/LICENSE",
         "src/inferrsi/data/skill_library/repositories/flare-local-inference/audit-flare-session-lifecycle/SKILL.md",
@@ -57,7 +57,7 @@
     "src/inferrsi/data/skill_library/repositories/flare-local-inference/audit-flare-session-lifecycle/references/lifecycle.md": "107ebe3c22e5dba8007c3b8ea61149f10bc55c51b557a4230f3e5de859bb0f7c",
     "src/inferrsi/data/skill_library/repositories/flare-local-inference/audit-flare-session-lifecycle/references/source-ledger.json": "61e51a97ffd7c1fa7866bdd440b024d0c5e0065635ac8d0ba53d2c69c7f9e470",
     "src/inferrsi/data/skill_library/repositories/flare-local-inference/audit-flare-session-lifecycle/references/source-notes.md": "fc7ceb819b91ef1731d8b7783f543c92ef6bb5c97ef5f897c055824f8a560168",
-    "src/inferrsi/data/skill_library/skill-index.json": "eaf446cb37baa90d40166119ca17cc0a434dbe3f77611423f648b0f225903f7c"
+    "src/inferrsi/data/skill_library/skill-index.json": "531190c468b6fb385b9b4aa71e666e8dd20d92aa5adc54bf4040f2096e3dd190"
   },
   "skill_metadata": {
     "name": "audit-flare-session-lifecycle",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json
index 79f6fc638..4d90b23b0 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json
@@ -16,8 +16,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/e71d0631a1c0854c9616d8ef5e174d3a1e14af4b/src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/SKILL.md",
-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/SKILL.md",
+      "commit": "f0e87c48809601d38035960d26737e0698489165",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/metadata.json",
@@ -52,7 +52,7 @@
     "src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/references/papers-20261015/cases/partitioning-after-fusion.md": "4d4cabe0991eab554dcfbd4fa9c8199e61fa4767709b0c4cd646e2588bb398a2",
     "src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/references/papers-20261015/knowledge/attention-cost-model-boundaries.md": "5ed8f888443e38ccb72545b6025447aab7b92936f78c151fed680e582126239b",
     "src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/references/sources.md": "53436e0de4e6dda2d29426591bf61f8526378cdc6f9ec7967b88b1bcd4c61e6f",
-    "src/inferrsi/data/skill_library/skill-index.json": "eaf446cb37baa90d40166119ca17cc0a434dbe3f77611423f648b0f225903f7c"
+    "src/inferrsi/data/skill_library/skill-index.json": "531190c468b6fb385b9b4aa71e666e8dd20d92aa5adc54bf4040f2096e3dd190"
   },
   "skill_metadata": {
     "name": "diagnose-attention-bottlenecks",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json
index e8178bd30..f316df134 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/e71d0631a1c0854c9616d8ef5e174d3a1e14af4b/src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/SKILL.md",
-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/SKILL.md",
+      "commit": "f0e87c48809601d38035960d26737e0698489165",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/metadata.json",
@@ -40,7 +40,7 @@
   "source_files": {
     "src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/SKILL.md": "326e566fbe30d3ba04e4b50c3e87aad9df037f0ac4ad6fe129165ae97dc5f91d",
     "src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/metadata.json": "76e34c1c64aba473a9e126b032a776417caa0f913f6ac3cf4dba3a5d123b1ee0",
-    "src/inferrsi/data/skill_library/skill-index.json": "eaf446cb37baa90d40166119ca17cc0a434dbe3f77611423f648b0f225903f7c"
+    "src/inferrsi/data/skill_library/skill-index.json": "531190c468b6fb385b9b4aa71e666e8dd20d92aa5adc54bf4040f2096e3dd190"
   },
   "skill_metadata": {
     "name": "host-overhead-profiling",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/reason-hopper-kernels.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/reason-hopper-kernels.json
index f474ce5eb..f1799ffe4 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/reason-hopper-kernels.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/reason-hopper-kernels.json
@@ -36,8 +36,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/e71d0631a1c0854c9616d8ef5e174d3a1e14af4b/src/inferrsi/data/skill_library/hardware/cuda/reason-hopper-kernels/SKILL.md",
-      "commit": "e71d0631a1c0854c9616d8ef5e174d3a1e14af4b",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/f0e87c48809601d38035960d26737e0698489165/src/inferrsi/data/skill_library/hardware/cuda/reason-hopper-kernels/SKILL.md",
+      "commit": "f0e87c48809601d38035960d26737e0698489165",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/cuda/reason-hopper-kernels/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/cuda/reason-hopper-kernels/metadata.json",
@@ -72,7 +72,7 @@
     "src/inferrsi/data/skill_library/hardware/cuda/reason-hopper-kernels/references/source-inventory.json": "1dc09c895c970a0c9708158bcc6dd65cdb736274fd2c35d44542c70407d3849d",
     "src/inferrsi/data/skill_library/hardware/cuda/reason-hopper-kernels/references/sources.md": "6b74b9e774f2a80db0860510d9e6940d36284430f29c1e124f115a9eaf25833d",
     "src/inferrsi/data/skill_library/hardware/cuda/reason-hopper-kernels/references/synchronization.md": "4322f6b3c0e4368bf8c192b4ec752529767f50d19c0c38dad8fdf9cd781e41d9",
-    "src/inferrsi/data/skill_library/skill-index.json": "eaf446cb37baa90d40166119ca17cc0a434dbe3f77611423f648b0f225903f7c"
+    "src/inferrsi/data/skill_library/skill-index.json": "531190c468b6fb385b9b4aa71e666e8dd20d92aa5adc54bf4040f2096e3dd190"
   },
   "skill_metadata": {
     "name": "reason-hopper-kernels",
diff --git a/src/inferrsi/data/skill_library/README.md b/src/inferrsi/data/skill_library/README.md
index 37dff9cdd..729affa56 100644
--- a/src/inferrsi/data/skill_library/README.md
+++ b/src/inferrsi/data/skill_library/README.md
@@ -1,6 +1,6 @@
 # InferRSI skill library
 
-The English-only library contains **118 skill documents**: 74 registered roots,
+The English-only library contains **120 skill documents**: 76 registered roots,
 21 separately indexed engine/router documents and 23 AREX graph sub-skills.
 Complete procedures, metadata, references, cases and source notices ship with the package.
 
@@ -20,7 +20,7 @@ existing resource directory.
 
 ## Read registered skills
 
-[`skill-index.json`](skill-index.json) maps 74 stable skill IDs to their canonical
+[`skill-index.json`](skill-index.json) maps 76 stable skill IDs to their canonical
 paths and backend scopes. Install the optional `skills` extra for these commands:
 
 ```bash
@@ -137,7 +137,7 @@ scheduling/placement proposals remain separate from both implementation pins.
 
 Five repository entry skills, 15 focused sub-skills and one research router
 provide source-grounded procedures. These 21 documents are available through
-the links and catalog records below, separately from the 74-ID registry.
+the links and catalog records below, separately from the 76-ID registry.
 The registered ComfyUI and stable-diffusion.cpp audits are listed alongside
 these imports and use generated abstracts rather than runtime repository packs.
 
diff --git a/src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/SKILL.md b/src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/SKILL.md
index 3bac06567..66eab0871 100644
--- a/src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/SKILL.md
+++ b/src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/SKILL.md
@@ -1,11 +1,13 @@
 ---
 name: ascend-video-diffusion-optimization
-description: Run and verify goal-driven Ascend video diffusion optimization. Use when the user asks for latency, RTF, throughput, or HBM targets across VLM, DiT, MoE, attention, or VAE. Not for text-only LLMs.
+description: 'Run and verify goal-driven Ascend video diffusion optimization. Specializes the backend-agnostic video-diffusion-optimization skeleton with Ascend NPU operator, layout and profiler references. Use when the user asks for latency, RTF, throughput, or HBM targets across VLM, DiT, MoE, attention, or VAE on Ascend NPU. Not for text-only LLMs.'
 ---
 
 # Ascend Video Diffusion Optimization
 
-Status: candidate workflow guidance. The procedure is first-hand and has not been independently validated beyond the [field notes](references/field-notes-video-diffusion.md). Keep model identifiers, campaign revisions, and numeric gates out of this file; they belong to an acceptance issue and its frozen evidence.
+Status: candidate workflow guidance, Ascend-specific. The procedure is first-hand and has not been independently validated beyond the [field notes](references/field-notes-video-diffusion.md). Keep model identifiers, campaign revisions, and numeric gates out of this file; they belong to an acceptance issue and its frozen evidence.
+
+This skill is the Ascend specialization of the backend-agnostic [video diffusion optimization skeleton](../../../methods/video-diffusion-optimization/SKILL.md). Follow that skeleton for the goal contract, baseline discipline, optimization loop, candidate-selection strategy, correctness protection, final acceptance, and final report. This file adds the Ascend-specific operator, layout, and profiler references; it does not repeat the full procedure.
 
 Own the performance objective through implementation and final verification. Do not stop after profiling, proposing changes, or showing a faster microbenchmark. Continue the measure-change-verify loop until the target is met, the authorized budget is exhausted, or an external blocker prevents execution.
 
@@ -13,167 +15,15 @@ Read the field notes only for prior failures and starting hypotheses. Treat ever
 
 Verify every stage against the packaged [benchmark design](../../../methods/inference-benchmark-design/SKILL.md) and [evidence discipline](../../../workflows/rsi-evidence/SKILL.md). A microbenchmark or operator parity check is not end-to-end evidence.
 
-## 1. Freeze The Goal Contract
-
-Write the contract before editing code:
-
-- Primary metric and direction, such as a latency, RTF, throughput, or peak-HBM bar.
-- Exact timing boundary and RTF denominator.
-- Required workload set: representative short input, production-shaped input, longest supported input, and held-out cases.
-- Quality gates, such as tensor tolerance, image or video metrics, recognition success, prompt adherence, or human review.
-- Resource gates: no OOM, maximum HBM, device count, and prohibited offload.
-- Approximation policy: exact, numerically tolerant, perceptually gated, or task-quality gated.
-- Warmup count, measured repetitions, aggregation rule, and maximum acceptable variance.
-- Optimization budget: allowed code changes, lossy methods, experiment count, and wall time.
-
-Numeric gates come from the governing acceptance issue. Do not invent them in this skill, in workflow defaults, or in reusable recipes.
-
-If the user supplied a target, preserve it exactly. If no numeric target exists, establish one before claiming success. A vague request to "make it faster" permits exploration, not a `PASS`.
-
-Freeze model and checkpoint revision, architecture mode, hardware SKU, device mapping, runtime and custom-op revisions, input, prompt, size, frames, FPS, steps, guidance, seed, dtype, scheduler, and output validator.
-
-Align actual initial noise or latent across frameworks. Equal seed values are insufficient when RNG advancement differs.
-
-## 2. Build A Reproducible Baseline
-
-Start from a clean process. Exclude warmup from steady-state measurements and report cold start separately.
-
-Measure synchronized wall time and peak HBM for:
-
-1. Input decode and preprocessing.
-2. Each condition encoder and vision path.
-3. Source-video VAE encode when present.
-4. DiT denoising, with attention, MoE or MLP, normalization, and residual attribution when needed.
-5. VAE decode.
-6. Postprocessing, layout conversion, device-to-host transfer, and encoding.
-
-Collect at least three measured repetitions; use five or more for final acceptance. Preserve raw samples and report median plus range or IQR. On a shared machine, interleave baseline and candidate in the same allocation window.
-
-Do not optimize while the baseline is unstable. Investigate device health, neighbor load, thermal or frequency state, compilation, cache state, and synchronization until variance is within the contract.
-
-Compute an Amdahl ceiling from non-overlapping stage wall-time fractions. Use it to rank work and to expose when the requested target requires multiple stages or an algorithmic change.
-
-## 3. Run The Optimization Loop
-
-Maintain an experiment ledger. For every round record:
-
-- Hypothesis and profiler evidence.
-- Expected end-to-end gain and resource cost.
-- Exact code or configuration delta.
-- Quality and correctness result.
-- Raw performance samples, aggregate, peak HBM, and variance.
-- Verdict: keep, revert, or inconclusive.
-
-Execute this loop:
-
-1. Profile the current accepted state.
-2. Select the largest removable exposed cost, not the largest summed kernel duration.
-3. Make one bounded change, keeping one declared plane per step.
-4. Run the fastest correctness gate that can reject it.
-5. Run a short A/B probe with identical workload and synchronization.
-6. Revert regressions and failed quality gates.
-7. Keep a win only when it exceeds measurement noise and does not violate any gate.
-8. Re-profile the accepted state because the bottleneck may move.
-9. Evaluate the goal contract with `scripts/evaluate_target.py`.
-10. Continue until final acceptance passes or the budget is exhausted.
-
-Do not leave rejected experimental code enabled. Preserve only logs, evidence, and accepted production changes.
-
-## 4. Choose Candidates From Evidence
-
-### Condition And Scheduling
-
-- Verify visual pixel, frame, and token budgets before changing kernels.
-- Keep frequently reused condition encoders resident only when transfer or reload cost dominates and HBM headroom permits.
-- Quantize large language-MLP weights selectively; keep attention, embeddings, normalization, routers, and vision paths in higher precision until separately validated.
-- Treat condition/VAE overlap as a conditional candidate, never a default optimization. Draw the request-level dependency DAG before creating streams. Record each stage's inputs, outputs, mutable state, consumers, and earliest legal start.
-- Permit overlap only when condition encoding does not consume VAE latents or metadata, VAE does not consume condition outputs, neither stage mutates shared buffers or module state, and both outputs are needed only at a later join.
-- Prove runtime safety separately from logical independence. Verify every operator supports the selected streams, establish producer-consumer events, record tensor lifetimes on side streams, and join both streams before their first common consumer.
-- Check resource compatibility before enabling overlap. Concurrent work must not cause OOM, allocator pressure, workspace collision, or enough compute and bandwidth contention to erase the wall-time gain.
-- If only subgraphs are independent, overlap only those subgraphs. Keep the dependent prefix or suffix serial. If any dependency or lifetime is uncertain, preserve serial execution.
-- Accept overlap only when the profiler timeline shows real concurrency and synchronized end-to-end A/B measurements improve beyond noise while quality and HBM gates pass. The maximum theoretical saving is bounded by the shorter exposed stage; configured streams alone are not evidence.
-- Localize cold start around vision embeddings, patch merging, compilation, weight loading, and format conversion.
-
-### DiT, MoE, And Quantization
-
-- Prefer large linear projections and expert weights as initial quantization candidates.
-- Instantiate final quantized modules directly to avoid simultaneous full-precision and quantized copies.
-- Release loader references before format conversion and before loading the next component.
-- Materialize contiguous weights before packed or `FRACTAL_NZ` conversion when source strides can differ from physical order.
-- Measure intermediate cast and copy cost. Treat changed intermediate precision as approximate unless equivalence is proven.
-- Validate attention and MoE independently before combining optimizations.
-
-### Attention
-
-- Establish a dense fused baseline first.
-- Use sparse attention only when token geometry and sequence length amortize setup cost.
-- Derive dense-prefix and sparse-grid regions from actual token packing.
-- Require eligibility checks and a dense fallback.
-- Tune activation step, skipped layers, and sparsity separately.
-- Re-profile after a kernel win; VAE, MoE, casts, or synchronization may become dominant.
-
-### VAE And Long Video
-
-- Use no-tiling decode only when the measured shape has safe HBM headroom.
-- Enable temporal or spatial chunking dynamically for larger shapes.
-- Replace repeated growing `torch.cat` operations with list accumulation and one final concatenation.
-- Attribute `TransData` and layout copies before designing fusion or format-preserving wrappers.
-- Distinguish capacity failure, model temporal-quality failure, and algorithmic cost growth.
-- Derive chunk length and overlap experimentally. For text or sharp structures, compare midpoint hard cuts against blending.
-- Do not move VAE to CPU when RTF and numerical consistency are hard gates unless explicitly authorized.
-
-## 5. Protect Correctness
-
-When output diverges:
-
-1. Verify checkpoint structure and architecture mode.
-2. Align media preprocessing, frame sampling, resize, normalization, text cleanup, tokenization, masks, and padding.
-3. Inject identical initial latents and compare one denoising step.
-4. Compare scheduler coefficients, patch order, and unpatchify order.
-5. Find the first divergent block, then inspect normalization, attention, routing, experts, residual, and projection.
-6. For MoE, verify indices, routing weights, activation semantics, packed weight order, transpose rules, and accelerator layout.
-7. Remove dumps, golden injection, and debug-only paths after verification.
-
-Do not use output hash equality as the only quality proof. Do not label sparse attention, lower precision, or changed accumulation order as lossless without evidence.
-
-## 6. Final Acceptance
-
-After the target first appears met, restart from the final code and configuration. Do not validate a stale process or a best-seen intermediate state.
-
-Run the full acceptance set:
-
-- At least five interleaved baseline/candidate groups in the same measurement window.
-- Representative short, production-shaped, longest supported, and held-out inputs.
-- Cold-start and steady-state measurements when loading or compilation changed.
-- Primary performance metric, stage breakdown, peak HBM, and raw samples.
-- Every automatic quality gate plus required visual or task review.
-- No OOM, corruption, fallback, hidden CPU offload, skipped work, or invalid output.
-
-A local pre-check is available:
-
-```bash
-cp {skill_path}/assets/campaign.template.json campaign.json
-# Replace every placeholder with measured samples and the issue-scoped gates.
-python3 {skill_path}/scripts/evaluate_target.py campaign.json
-```
-
-The script checks target attainment, minimum improvement, variance, quality gates, and resource gates. It is an aid, not the verdict. The authoritative verdict comes from the acceptance issue's frozen gates and its `evidence/<campaign-id>/` tree, and it stays `INCONCLUSIVE` while any required level or artifact is missing.
-
-Return `PASS` only when the final restarted artifact satisfies the frozen gates, with pinned baseline and candidate revisions and complete evidence. A microbenchmark win, one fast run, a profiler estimate, or an earlier best result is insufficient.
-
-Return `FAIL` when complete enough evidence shows a gate was not met. Report the measured gap, accepted gains, rejected rounds, binding bottleneck, remaining ceiling, and the next change required.
+## Ascend-Specific Layout And Profiler References
 
-Return `INCONCLUSIVE` when a freeze is missing, runs are partial, the environment does not qualify, or required levels were not executed. Report the exact missing prerequisite and preserve the completed evidence.
+Where the common skeleton says "operator names, memory layouts, and profiler references are backend-specific", apply these Ascend facts:
 
-## 7. Final Report
+- `FRACTAL_NZ` is the Ascend packed weight layout. Materialize contiguous weights before converting to `FRACTAL_NZ` when source strides can differ from physical order; a physical-layout mismatch corrupts output.
+- `TransData` performs layout conversion between formats. Attribute `TransData` and layout-copy cost before designing fusion or format-preserving wrappers.
+- Profiling and stream instrumentation follow `CANN` conventions. Establish producer-consumer events, record tensor lifetimes on side streams, and join streams before their first common consumer.
+- Sparse-attention and quantization candidate selection remain backend-agnostic decisions; only the kernel names, packed-layout materialization, and profiler attributions are Ascend-specific.
 
-Report:
+For the candidate-selection guidance (condition/scheduling, DiT/MoE/quantization, attention, VAE/long-video), follow the common skeleton and read the [field notes](references/field-notes-video-diffusion.md) for the Ascend-specific failures to avoid.
 
-- Final verdict: `PASS`, `FAIL`, or `INCONCLUSIVE`.
-- Frozen goal and quality contract, with its acceptance issue.
-- Baseline and final raw samples, aggregates, variance, RTF, and peak HBM.
-- End-to-end improvement and whether it exceeds noise.
-- Quality and longest-input results.
-- Accepted and reverted changes.
-- Final artifact revision and exact runtime configuration.
-- Remaining gap and ceiling when the target is not met.
+The common skeleton's `scripts/evaluate_target.py` and `assets/campaign.template.json` are shared and backend-agnostic; use them as documented there.
diff --git a/src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/metadata.json b/src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/metadata.json
index 5bb62f030..36a513071 100644
--- a/src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/metadata.json
+++ b/src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/metadata.json
@@ -23,10 +23,11 @@
   },
   "applicability": {
     "scope": "Ascend NPU video diffusion inference and serving optimization",
-    "hardware": "Ascend NPU; procedures are hardware-agnostic apart from layout and profiler references",
+    "hardware": "Ascend NPU; the measure-change-verify workflow skeleton is backend-agnostic and lives in methods/video-diffusion-optimization, while the operator, layout and profiler references here are Ascend-specific",
     "prerequisites": "A reproducible benchmark, a frozen quality check, and numeric gates defined in the governing acceptance issue"
   },
   "limitations": [
+    "Ascend specialization of the backend-agnostic methods/video-diffusion-optimization skeleton; every operator, layout and profiler reference (TransData, FRACTAL_NZ, CANN) is Ascend-specific and must be re-derived per backend.",
     "Candidate workflow guidance; not independently validated beyond the field notes.",
     "Field notes are non-reproducible as published and must not be cited as evidence.",
     "Model identifiers, campaign revisions, and numeric gates are intentionally excluded and remain issue-scoped.",
@@ -35,5 +36,10 @@
   "provenance_readsets": [
     "references/field-notes-video-diffusion.md"
   ],
+  "references": [
+    "../../../methods/video-diffusion-optimization/SKILL.md",
+    "../../../methods/video-diffusion-optimization/scripts/evaluate_target.py",
+    "../../../methods/video-diffusion-optimization/assets/campaign.template.json"
+  ],
   "consumption_mode": "packaged"
 }
diff --git a/src/inferrsi/data/skill_library/methods/video-diffusion-optimization/SKILL.md b/src/inferrsi/data/skill_library/methods/video-diffusion-optimization/SKILL.md
new file mode 100644
index 000000000..edc36a2e4
--- /dev/null
+++ b/src/inferrsi/data/skill_library/methods/video-diffusion-optimization/SKILL.md
@@ -0,0 +1,179 @@
+---
+name: video-diffusion-optimization
+description: 'Run and verify goal-driven video diffusion optimization, backend-agnostic. Use when the user asks for latency, RTF, throughput, or memory targets across VLM, DiT, MoE, attention, or VAE, on any accelerator. Not for text-only LLMs.'
+---
+
+# Video Diffusion Optimization
+
+Status: candidate workflow guidance, backend-agnostic. The procedure is first-hand and has not been independently validated. Keep model identifiers, campaign revisions, and numeric gates out of this file; they belong to an acceptance issue and its frozen evidence.
+
+Own the performance objective through implementation and final verification. Do not stop after profiling, proposing changes, or showing a faster microbenchmark. Continue the measure-change-verify loop until the target is met, the authorized budget is exhausted, or an external blocker prevents execution.
+
+This skeleton is backend-agnostic. Operator names, memory layouts, and profiler references are backend-specific. The `ascend-video-diffusion-optimization` skill under `hardware/ascend/` specializes this skeleton with Ascend annotations (`TransData`, `FRACTAL_NZ`, `CANN`) and first-hand field notes; re-derive those per backend before following the candidate-selection sections below.
+
+Verify every stage against the packaged [benchmark design](../inference-benchmark-design/SKILL.md) and [evidence discipline](../../workflows/rsi-evidence/SKILL.md). A microbenchmark or operator parity check is not end-to-end evidence.
+
+## 1. Freeze The Goal Contract
+
+Write the contract before editing code:
+
+- Primary metric and direction, such as a latency, RTF, throughput, or peak-memory bar.
+- Exact timing boundary and RTF denominator.
+- Required workload set: representative short input, production-shaped input, longest supported input, and held-out cases.
+- Quality gates, such as tensor tolerance, image or video metrics, recognition success, prompt adherence, or human review.
+- Resource gates: no OOM, maximum memory, device count, and prohibited offload.
+- Approximation policy: exact, numerically tolerant, perceptually gated, or task-quality gated.
+- Warmup count, measured repetitions, aggregation rule, and maximum acceptable variance.
+- Optimization budget: allowed code changes, lossy methods, experiment count, and wall time.
+
+Numeric gates come from the governing acceptance issue. Do not invent them in this skill, in workflow defaults, or in reusable recipes.
+
+If the user supplied a target, preserve it exactly. If no numeric target exists, establish one before claiming success. A vague request to "make it faster" permits exploration, not a `PASS`.
+
+Freeze model and checkpoint revision, architecture mode, hardware SKU, device mapping, runtime and custom-op revisions, input, prompt, size, frames, FPS, steps, guidance, seed, dtype, scheduler, and output validator.
+
+Align actual initial noise or latent across frameworks. Equal seed values are insufficient when RNG advancement differs.
+
+## 2. Build A Reproducible Baseline
+
+Start from a clean process. Exclude warmup from steady-state measurements and report cold start separately.
+
+Measure synchronized wall time and peak memory for:
+
+1. Input decode and preprocessing.
+2. Each condition encoder and vision path.
+3. Source-video VAE encode when present.
+4. DiT denoising, with attention, MoE or MLP, normalization, and residual attribution when needed.
+5. VAE decode.
+6. Postprocessing, layout conversion, device-to-host transfer, and encoding.
+
+Collect at least three measured repetitions; use five or more for final acceptance. Preserve raw samples and report median plus range or IQR. On a shared machine, interleave baseline and candidate in the same allocation window.
+
+Do not optimize while the baseline is unstable. Investigate device health, neighbor load, thermal or frequency state, compilation, cache state, and synchronization until variance is within the contract.
+
+Compute an Amdahl ceiling from non-overlapping stage wall-time fractions. Use it to rank work and to expose when the requested target requires multiple stages or an algorithmic change.
+
+## 3. Run The Optimization Loop
+
+Maintain an experiment ledger. For every round record:
+
+- Hypothesis and profiler evidence.
+- Expected end-to-end gain and resource cost.
+- Exact code or configuration delta.
+- Quality and correctness result.
+- Raw performance samples, aggregate, peak memory, and variance.
+- Verdict: keep, revert, or inconclusive.
+
+Execute this loop:
+
+1. Profile the current accepted state.
+2. Select the largest removable exposed cost, not the largest summed kernel duration.
+3. Make one bounded change, keeping one declared plane per step.
+4. Run the fastest correctness gate that can reject it.
+5. Run a short A/B probe with identical workload and synchronization.
+6. Revert regressions and failed quality gates.
+7. Keep a win only when it exceeds measurement noise and does not violate any gate.
+8. Re-profile the accepted state because the bottleneck may move.
+9. Evaluate the goal contract with `scripts/evaluate_target.py`.
+10. Continue until final acceptance passes or the budget is exhausted.
+
+Do not leave rejected experimental code enabled. Preserve only logs, evidence, and accepted production changes.
+
+## 4. Choose Candidates From Evidence
+
+### Condition And Scheduling
+
+- Verify visual pixel, frame, and token budgets before changing kernels.
+- Keep frequently reused condition encoders resident only when transfer or reload cost dominates and memory headroom permits.
+- Quantize large language-MLP weights selectively; keep attention, embeddings, normalization, routers, and vision paths in higher precision until separately validated.
+- Treat condition/VAE overlap as a conditional candidate, never a default optimization. Draw the request-level dependency DAG before creating streams. Record each stage's inputs, outputs, mutable state, consumers, and earliest legal start.
+- Permit overlap only when condition encoding does not consume VAE latents or metadata, VAE does not consume condition outputs, neither stage mutates shared buffers or module state, and both outputs are needed only at a later join.
+- Prove runtime safety separately from logical independence. Verify every operator supports the selected streams, establish producer-consumer events, record tensor lifetimes on side streams, and join both streams before their first common consumer.
+- Check resource compatibility before enabling overlap. Concurrent work must not cause OOM, allocator pressure, workspace collision, or enough compute and bandwidth contention to erase the wall-time gain.
+- If only subgraphs are independent, overlap only those subgraphs. Keep the dependent prefix or suffix serial. If any dependency or lifetime is uncertain, preserve serial execution.
+- Accept overlap only when the profiler timeline shows real concurrency and synchronized end-to-end A/B measurements improve beyond noise while quality and memory gates pass. The maximum theoretical saving is bounded by the shorter exposed stage; configured streams alone are not evidence.
+- Localize cold start around vision embeddings, patch merging, compilation, weight loading, and format conversion.
+
+### DiT, MoE, And Quantization
+
+- Prefer large linear projections and expert weights as initial quantization candidates.
+- Instantiate final quantized modules directly to avoid simultaneous full-precision and quantized copies.
+- Release loader references before format conversion and before loading the next component.
+- Materialize contiguous weights before any backend-specific packed-layout conversion when source strides can differ from physical order.
+- Measure intermediate cast and copy cost. Treat changed intermediate precision as approximate unless equivalence is proven.
+- Validate attention and MoE independently before combining optimizations.
+
+### Attention
+
+- Establish a dense fused baseline first.
+- Use sparse attention only when token geometry and sequence length amortize setup cost.
+- Derive dense-prefix and sparse-grid regions from actual token packing.
+- Require eligibility checks and a dense fallback.
+- Tune activation step, skipped layers, and sparsity separately.
+- Re-profile after a kernel win; VAE, MoE, casts, or synchronization may become dominant.
+
+### VAE And Long Video
+
+- Use no-tiling decode only when the measured shape has safe memory headroom.
+- Enable temporal or spatial chunking dynamically for larger shapes.
+- Replace repeated growing concatenation operations with list accumulation and one final concatenation.
+- Attribute layout-conversion and copy costs before designing fusion or format-preserving wrappers.
+- Distinguish capacity failure, model temporal-quality failure, and algorithmic cost growth.
+- Derive chunk length and overlap experimentally. For text or sharp structures, compare midpoint hard cuts against blending.
+- Do not move VAE to host when RTF and numerical consistency are hard gates unless explicitly authorized.
+
+## 5. Protect Correctness
+
+When output diverges:
+
+1. Verify checkpoint structure and architecture mode.
+2. Align media preprocessing, frame sampling, resize, normalization, text cleanup, tokenization, masks, and padding.
+3. Inject identical initial latents and compare one denoising step.
+4. Compare scheduler coefficients, patch order, and unpatchify order.
+5. Find the first divergent block, then inspect normalization, attention, routing, experts, residual, and projection.
+6. For MoE, verify indices, routing weights, activation semantics, packed weight order, transpose rules, and accelerator layout.
+7. Remove dumps, golden injection, and debug-only paths after verification.
+
+Do not use output hash equality as the only quality proof. Do not label sparse attention, lower precision, or changed accumulation order as lossless without evidence.
+
+## 6. Final Acceptance
+
+After the target first appears met, restart from the final code and configuration. Do not validate a stale process or a best-seen intermediate state.
+
+Run the full acceptance set:
+
+- At least five interleaved baseline/candidate groups in the same measurement window.
+- Representative short, production-shaped, longest supported, and held-out inputs.
+- Cold-start and steady-state measurements when loading or compilation changed.
+- Primary performance metric, stage breakdown, peak memory, and raw samples.
+- Every automatic quality gate plus required visual or task review.
+- No OOM, corruption, fallback, hidden host offload, skipped work, or invalid output.
+
+A local pre-check is available:
+
+```bash
+cp {skill_path}/assets/campaign.template.json campaign.json
+# Replace every placeholder with measured samples and the issue-scoped gates.
+python3 {skill_path}/scripts/evaluate_target.py campaign.json
+```
+
+The script checks target attainment, minimum improvement, variance, quality gates, and resource gates. It is an aid, not the verdict. The authoritative verdict comes from the acceptance issue's frozen gates and its `evidence/<campaign-id>/` tree, and it stays `INCONCLUSIVE` while any required level or artifact is missing.
+
+Return `PASS` only when the final restarted artifact satisfies the frozen gates, with pinned baseline and candidate revisions and complete evidence. A microbenchmark win, one fast run, a profiler estimate, or an earlier best result is insufficient.
+
+Return `FAIL` when complete enough evidence shows a gate was not met. Report the measured gap, accepted gains, rejected rounds, binding bottleneck, remaining ceiling, and the next change required.
+
+Return `INCONCLUSIVE` when a freeze is missing, runs are partial, the environment does not qualify, or required levels were not executed. Report the exact missing prerequisite and preserve the completed evidence.
+
+## 7. Final Report
+
+Report:
+
+- Final verdict: `PASS`, `FAIL`, or `INCONCLUSIVE`.
+- Frozen goal and quality contract, with its acceptance issue.
+- Baseline and final raw samples, aggregates, variance, RTF, and peak memory.
+- End-to-end improvement and whether it exceeds noise.
+- Quality and longest-input results.
+- Accepted and reverted changes.
+- Final artifact revision and exact runtime configuration.
+- Remaining gap and ceiling when the target is not met.
diff --git a/src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/assets/campaign.template.json b/src/inferrsi/data/skill_library/methods/video-diffusion-optimization/assets/campaign.template.json
similarity index 100%
rename from src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/assets/campaign.template.json
rename to src/inferrsi/data/skill_library/methods/video-diffusion-optimization/assets/campaign.template.json
diff --git a/src/inferrsi/data/skill_library/methods/video-diffusion-optimization/metadata.json b/src/inferrsi/data/skill_library/methods/video-diffusion-optimization/metadata.json
new file mode 100644
index 000000000..a3fa54151
--- /dev/null
+++ b/src/inferrsi/data/skill_library/methods/video-diffusion-optimization/metadata.json
@@ -0,0 +1,36 @@
+{
+  "schema_version": 1,
+  "profile": "local-skill-v1",
+  "kind": "skill",
+  "status": "candidate",
+  "origin": ["first-party"],
+  "tags": [
+    "video-diffusion",
+    "dit",
+    "moe",
+    "attention",
+    "vae",
+    "performance",
+    "profiling",
+    "serving",
+    "optimization"
+  ],
+  "empirical_validation": "not_run",
+  "verification": {
+    "locally_verified": false,
+    "evidence_level": "guidance",
+    "note": "Procedure is first-hand workflow guidance. The linked field notes are not reproducible as published. No acceptance campaign under this repository's evidence contract backs this skill, and no public performance claim is made."
+  },
+  "applicability": {
+    "scope": "Backend-agnostic video diffusion inference and serving optimization",
+    "hardware": "Any accelerator (Ascend NPU, CUDA GPU, and others); operator names, memory layouts, and profiler references are re-derived per backend",
+    "prerequisites": "A reproducible benchmark, a frozen quality check, and numeric gates defined in the governing acceptance issue"
+  },
+  "limitations": [
+    "Backend-agnostic skeleton only. The first-hand field notes are Ascend-specific and live in the ascend-video-diffusion-optimization skill; every operator, layout and profiler reference (TransData, FRACTAL_NZ, CANN) must be re-derived per backend.",
+    "Candidate workflow guidance; not independently validated.",
+    "Model identifiers, campaign revisions, and numeric gates are intentionally excluded and remain issue-scoped."
+  ],
+  "provenance_readsets": [],
+  "consumption_mode": "packaged"
+}
diff --git a/src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/scripts/evaluate_target.py b/src/inferrsi/data/skill_library/methods/video-diffusion-optimization/scripts/evaluate_target.py
similarity index 100%
rename from src/inferrsi/data/skill_library/hardware/ascend/ascend-video-diffusion-optimization/scripts/evaluate_target.py
rename to src/inferrsi/data/skill_library/methods/video-diffusion-optimization/scripts/evaluate_target.py
diff --git a/src/inferrsi/data/skill_library/skill-index.json b/src/inferrsi/data/skill_library/skill-index.json
index 900f3901e..e683e9fc6 100644
--- a/src/inferrsi/data/skill_library/skill-index.json
+++ b/src/inferrsi/data/skill_library/skill-index.json
@@ -293,6 +293,10 @@
       "path": "methods/training-resource-budget",
       "backend": "common"
     },
+    "video-diffusion-optimization": {
+      "path": "methods/video-diffusion-optimization",
+      "backend": "common"
+    },
     "vllm-metal": {
       "path": "repositories/vllm-metal",
       "backend": "common"
diff --git a/tests/check_installed.py b/tests/check_installed.py
index b30ff84c6..064c2dc4d 100644
--- a/tests/check_installed.py
+++ b/tests/check_installed.py
@@ -17,7 +17,7 @@
     "This check requires an installed package"
 )
 records = knowledge_records()
-assert len(records) == 123, "Knowledge is missing from the installation"
+assert len(records) == 124, "Knowledge is missing from the installation"
 assert (
     files("inferrsi")
     .joinpath("data", "repo_packs", "vllm_omni", "knowledge", "README.md")
@@ -42,7 +42,7 @@
         "package:" + record["id"], mlx_document, revision=bundle.revision
     ) == files("inferrsi").joinpath(*mlx_document.split("/")).read_bytes()
 skill_index = search_knowledge(repo="inferrsi", limit=100)
-assert len(skill_index) == 75, "Missing installed skill abstracts"
+assert len(skill_index) == 76, "Missing installed skill abstracts"
 assert all(record["index_type"] == "packaged-skill" for record in skill_index)
 indexed = KnowledgeReader().read("inferrsi.ascend.skills.ascend_operator_profiling")
 assert "data/skill_library/hardware/ascend/ascend-operator-profiling/SKILL.md" in indexed.content
@@ -190,7 +190,7 @@
         data = resource.read_bytes().replace(b"\r\n", b"\n")
         assert hashlib.sha256(data).hexdigest() == expected_hash, relative
 registry = json.loads(library.joinpath("skill-index.json").read_text(encoding="utf-8"))["skills"]
-assert len(registry) == 75
+assert len(registry) == 76
 for entry in registry.values():
     assert library.joinpath(*entry["path"].split("/"), "SKILL.md").is_file()
 router = library.joinpath("workflows", "inference-engine-research")
diff --git a/tests/test_ascend_video_diffusion_skill.py b/tests/test_ascend_video_diffusion_skill.py
index 90e3e34e5..5388514bd 100644
--- a/tests/test_ascend_video_diffusion_skill.py
+++ b/tests/test_ascend_video_diffusion_skill.py
@@ -11,45 +11,62 @@
 SKILL_ROOT = ROOT / "src/inferrsi/data/skill_library"
 SKILL_NAME = "ascend-video-diffusion-optimization"
 SKILL = SKILL_ROOT / "hardware/ascend" / SKILL_NAME
-TEMPLATE = SKILL / "assets/campaign.template.json"
-EVALUATOR = SKILL / "scripts/evaluate_target.py"
+COMMON_NAME = "video-diffusion-optimization"
+COMMON = SKILL_ROOT / "methods" / COMMON_NAME
+TEMPLATE = COMMON / "assets/campaign.template.json"
+EVALUATOR = COMMON / "scripts/evaluate_target.py"
 
 
-def test_skill_is_discoverable_and_resources_resolve():
+def test_skills_are_discoverable_and_resources_resolve():
     discovered = {record["name"] for record in skill_records(SKILL_ROOT)}
-    assert SKILL_NAME in discovered
+    assert {SKILL_NAME, COMMON_NAME} <= discovered
 
     record = get_skill(SKILL_ROOT, SKILL_NAME)
-
     assert record["name"] == SKILL_NAME
     assert record["status"] == "candidate"
     assert {"ascend", "video-diffusion", "performance"} <= set(record["tags"])
     assert set(record["resources"]) == {
-        "assets/campaign.template.json",
         "metadata.json",
         "references/field-notes-video-diffusion.md",
-        "scripts/evaluate_target.py",
     }
 
     description = record["description"]
     assert all(term in description for term in ("latency", "RTF", "throughput", "HBM"))
     assert "Not for text-only LLMs" in description
 
-    instructions = skill_instructions(SKILL_ROOT, SKILL_NAME)
-    for relative in (
+    common = get_skill(SKILL_ROOT, COMMON_NAME)
+    assert common["name"] == COMMON_NAME
+    assert common["status"] == "candidate"
+    assert set(common["resources"]) == {
         "assets/campaign.template.json",
-        "references/field-notes-video-diffusion.md",
+        "metadata.json",
         "scripts/evaluate_target.py",
-    ):
-        assert relative in instructions
-        assert (SKILL / relative).is_file()
+    }
+    assert common["description"]
+    assert "Not for text-only LLMs" in common["description"]
+
+    instructions = skill_instructions(SKILL_ROOT, SKILL_NAME)
+    assert "references/field-notes-video-diffusion.md" in instructions
+    assert (SKILL / "references/field-notes-video-diffusion.md").is_file()
+    # The Ascend skill delegates to the backend-agnostic common skeleton.
     for relative in (
+        "methods/video-diffusion-optimization/SKILL.md",
         "methods/inference-benchmark-design/SKILL.md",
         "workflows/rsi-evidence/SKILL.md",
     ):
         assert relative in instructions
         assert (SKILL_ROOT / relative).is_file()
 
+    common_instructions = skill_instructions(SKILL_ROOT, COMMON_NAME)
+    # The common skeleton links its sibling method and workflow with relative
+    # paths from methods/video-diffusion-optimization/.
+    for relative, target in (
+        ("../inference-benchmark-design/SKILL.md", "methods/inference-benchmark-design/SKILL.md"),
+        ("../../workflows/rsi-evidence/SKILL.md", "workflows/rsi-evidence/SKILL.md"),
+    ):
+        assert relative in common_instructions
+        assert (SKILL_ROOT / target).is_file()
+
 
 def campaign(case):
     data = json.loads(TEMPLATE.read_text(encoding="utf-8"))
diff --git a/tests/test_knowledge_contract.py b/tests/test_knowledge_contract.py
index d9d953dc0..dafd3bf11 100644
--- a/tests/test_knowledge_contract.py
+++ b/tests/test_knowledge_contract.py
@@ -31,7 +31,7 @@ def test_local_profiles_preserve_core_and_structured_ownership():
         assert metadata["kind"] == "skill"
         for readset in metadata["provenance_readsets"]:
             assert (sidecar.parent / readset).is_file()
-    assert len(normalized) == 59
+    assert len(normalized) == 60
 
 
 def test_local_sidecars_omit_fields_that_equal_reader_defaults():
diff --git a/tests/test_skill_index.py b/tests/test_skill_index.py
index 1137eba93..3df1f349f 100644
--- a/tests/test_skill_index.py
+++ b/tests/test_skill_index.py
@@ -23,7 +23,7 @@ def test_complete_index_retains_metadata_states_and_unknown_license():
     records = search_knowledge(repo="inferrsi", limit=100)
     names = {record["name"] for record in skill_records(ROOT)}
     registry = json.loads((ROOT / "skill-index.json").read_text(encoding="utf-8"))["skills"]
-    assert len(records) == len(names) == 75
+    assert len(records) == len(names) == 76
     assert {record["skill_metadata"]["name"] for record in records} == names
     states = []
     for record in records:
@@ -41,7 +41,7 @@ def test_complete_index_retains_metadata_states_and_unknown_license():
         }
         assert set(record["source_files"]) == set(record["sources"][0]["paths"])
         states.append(metadata.get("status"))
-    assert states.count("candidate") == 70
+    assert states.count("candidate") == 71
     assert states.count(None) == 5
     profiling = next(r for r in records if r["title"] == "ascend-operator-profiling")
     assert profiling["skill_metadata"]["license"] == "UNKNOWN"
@@ -188,7 +188,7 @@ def test_package_index_and_checkout_skill_have_distinct_read_boundaries():
     assert reader.resolve("claim-contract") == "checkout:claim-contract"
     assert reader.read("claim-contract").metadata["kind"] == "skill"
     collected = reader.collect(repo="inferrsi", kind="knowledge", limit=100, material=True)
-    assert len(collected["items"]) == 75
+    assert len(collected["items"]) == 76
     assert not collected["collisions"] and not collected["omissions"]
     assert all(item["authority"] == "package" for item in collected["items"])
     assert all("record.json" in item["resources"] for item in collected["items"])
@@ -218,9 +218,9 @@ def test_index_cli_search_show_context_and_execution_boundary(capsys):
 
 
 def test_hardware_filters_include_only_matching_and_shared_skills():
-    for backend, count in (("ascend", 70), ("cuda", 61), ("cpu", 56)):
+    for backend, count in (("ascend", 71), ("cuda", 62), ("cpu", 57)):
         records = search_knowledge(repo="inferrsi", backend=backend, limit=100)
         assert len(records) == count
         assert all(record["backend"] in (backend, "common") for record in records)
     assert not (PROJECT / "skills").exists()
-    assert len(list(ROOT.rglob("SKILL.md"))) == 119
+    assert len(list(ROOT.rglob("SKILL.md"))) == 120
diff --git a/tests/test_skill_library.py b/tests/test_skill_library.py
index f64c20e3a..efcca3d54 100644
--- a/tests/test_skill_library.py
+++ b/tests/test_skill_library.py
@@ -154,7 +154,7 @@ def test_library_root_exposes_only_owner_categories_and_required_entrypoints():
     assert {path.name for path in LIBRARY.iterdir() if path.is_dir()} == {
         "hardware", "frameworks", "repositories", "methods", "workflows",
     }
-    assert len(list(LIBRARY.rglob("SKILL.md"))) == 119
+    assert len(list(LIBRARY.rglob("SKILL.md"))) == 120
     assert not any(path.name == "zh-CN" for path in LIBRARY.rglob("*") if path.is_dir())
     references = LIBRARY / "workflows/inference-engine-research/references"
     assert (references / "import.md").is_file()