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EauDoon/README.md

EauDoon

Decision infrastructure for agent systems and operators.
Policy evaluation · recoverable execution · evidence-bound workflows

I turn operational problems into inspectable systems. Each project states its authority boundary, tests its failure paths, and separates what the evidence proves from what it does not.

Featured project · Agent infrastructure · Decision methods · Experiments

Featured project

A runnable Node.js reference path across policy evaluation, recourse-gated execution, and dispute evidence replay.

Follow a synthetic refund through the policy decision and execution outcome, then inspect the optional dispute-evidence simulation. The components use pinned versions and state their limits in the repository.

Open-source projects

Agent infrastructure

Project What it provides
Constitutional Agent Testbench Deterministic Python policy evaluation with precedence tracing for structured agent responses.
Consequence Rail JavaScript execution rail that reserves a remedy, checks the postcondition, and emits signed settlement receipts.
MandateBound TypeScript evidence-readiness simulation and deterministic dispute replay for UCP/AP2 agentic commerce.
TraceCanary Offline Python CLI and desktop GUI for detecting privacy regressions in OTLP GenAI trace exports.
Agent Team Reusable Python skill for bounded specialist workflows with independent audit and schema-backed evaluation.

Decision methods

Project What it provides
Crypto Research Desk Research-only workflow with four specialist lanes, independent risk review, and a fixed four-horizon forecast contract.
Corridor Lab Desktop GUI and CLI for comparing fictional cross-border payment routes across cost, speed, liquidity, and failure assumptions.
Unconventional Moves Reusable decision skill for practical, non-obvious approaches with reversible 48-hour tests.
The Smallest Agreement Local browser workshop for finding the lowest-cost structured agreement meeting an approval threshold and optional protected constraints.

Experiments and examples

Project What it provides
Common Cart Local-first pooled-purchase simulator that matches aggregate buyer constraints to synthetic offers without exposing buyer records.

How I build

  1. Define the user, decision, and authority boundary.
  2. Build the smallest inspectable system that can refuse invalid inputs.
  3. Test the normal path, failure path, and recovery path.
  4. Publish only claims that the artifacts can reproduce.

Authorship

I direct problem selection, product direction, requirements, business judgment, evaluation, rights review, and final acceptance for every project published here.

Pinned Loading

  1. agent-action-stack agent-action-stack Public

    Decide with Constitutional Agent Testbench, act with Consequence Rail, prove disputes with MandateBound.

    JavaScript

  2. consequence-rail consequence-rail Public

    Recourse-gated execution, recovery preflight, and signed settlement receipts for autonomous actions.

    JavaScript

  3. tracecanary tracecanary Public

    Desktop GUI and CLI for detecting privacy regressions in OpenTelemetry GenAI exports with synthetic canaries.

    Python