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skills: add Public231 C1, remeasure gate, and new-model integration - #172
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Document the lab L20X C1 measurement, the one-tip remeasure gate for agent optimization loops, and the issue-then-draft sequence for a new open model. Skill docs only. Co-authored-by: Hongsheng Liu <liuhongsheng4@huawei.com>
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the skill should not be spefified to a particular hardware |
Stop treating a non-L20X device as inconclusive. Record the measured device name and compute capability, and require that pair plus the same measurement protocol on both sides of a comparison. Co-authored-by: Hongsheng Liu <liuhongsheng4@huawei.com>
Document H200 / SM90 as the production label without gating on it. Every paste records the measured device string and compute capability, paired runs must share that identity, and a tip is not merge-clean without its RSI phase and the primary versus alternatives. Co-authored-by: Hongsheng Liu <liuhongsheng4@huawei.com>
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marked this pull request as ready for review
October 25, 2026 07:10
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Source: owner Hongsheng, this task (draft three repo skills; draft PR only). Later room clarification: production GPU identity is H200 / SM90, not a hard-coded L20X / sm_89 label. Each tip must name its RSI phase and the primary versus alternatives, or it is not merge-clean.
What outcome are you trying to achieve?
Repo-level skills so agents measure Public231 C1, gate later optimization on a remeasure with the same protocol and the same recorded hardware, and bring in a new open model in a fixed order.
What is the highest-leverage variable for that outcome?
A written, repo-accurate recipe agents load before those tasks, instead of inventing a hardware label, stacking unmeasured tips, or bundling a model into a serving issue.
How will this work move that variable rather than create busywork?
Three
SKILL.mdfiles under the existing.agents/skills/layout. No runtime code changes.Who is the customer or user, and what do they actually need?
Maintainers and coding agents on system1-omni. They need the measurement, the remeasure gate, and the new-model sequence in the repo.
Is a PR needed? Yes. Owner Hongsheng approved a draft pull request for these three skills.
Bug-fix evidence: Not a bug fix. Review withhold: do not treat a non-matching SKU as INCONCLUSIVE. The documented production target is H200 / SM90. Evidence records the measured
devicestring andcompute capability. Paired runs must share that recorded identity.Purpose
Add three skills agents can load for measurement and model bring-up:
.agents/skills/public231-c1/SKILL.md— Public231 C1: warmup 5, concurrency 1, three rounds, SHA, pass rate, p50/p95, thebench.pyclock, both no-thinking treatments, metrics-only room posts. Every paste recordsdeviceandcompute capability. Examples name the production target as H200 / SM90. A different nvidia-smi string is recorded as printed and is not INCONCLUSIVE..agents/skills/optimize-remeasure-gate/SKILL.md— paste p50/p95 plusdeviceandcompute capabilitybefore editing; do not stack the next tip until that tip is remeasured with the same protocol on the same recorded identity; incomplete evidence is INCONCLUSIVE. Each tip states its RSI phase (bring-up/scheduling, parallelism/comms, kernel, or launch/post) and which alternatives were considered versus the primary, or it is not merge-clean. The PR stays draft until a separate owner yes..agents/skills/new-model-integration/SKILL.md— own GitHub issue, draft PR, recipe and operator checklist, then Public231 C1, then continuous optimization on that branch under the same gate. Serving-chain issues stay separate from the new-model RFC.Placement matches the existing
.agents/skills/tree (add-new-model,self-review,precheck-pr). There is no.cursor/skills/tree in this repo.Test Plan
Docs-only skill files. No runtime code.
nameanddescription.benchmarks/,recipe/,CONTRIBUTING.md, and sibling skills.benchmarks/bench.py(--warmupdefault 3, so C1 passes--warmup 5; clockpost_to_body_json_and_schema_validation; three separate measuredruns).devicepluscompute capability.Test Result
System1-Omni Version / Commit:
c1dd645Relative links in the three skills resolve. Claims were checked against
benchmarks/README.md,benchmarks/bench.py,benchmarks/latency-leaderboard.md, and the open new-model vs serving-chain issue split (#61, #85, #125, #150 versusnew modelissues such as #114 and #136). No Rust or GPU run: the diff does not change runtime code.Demo / evidence
N/A. Skill documents only; no inference, serving, or benchmark campaign in this PR.
Self-review
Draft only. Do not merge and do not mark ready without a separate owner yes.