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EauDoon/README.md

EauDoon

AI systems builder from a business perspective

I turn operational problems into tested agent systems, decision tools, and reusable workflows.

This is my public build record: working artifacts, adversarial evaluations, documented failure cases, and explicit boundaries.

Featured open-source project

Agent Action Stack

One reference path across three libraries:

Decide  →  Act              →  Prove
testbench  Consequence Rail    MandateBound
  1. Decide: Constitutional Agent Testbench evaluates structured agent JSON against a declared policy.
  2. On pass → Act: Consequence Rail reserves recourse, executes, and settles or compensates.
  3. On dispute → Prove: MandateBound runs evidence-readiness simulation for review.
npm run bootstrap
npm run demo          # decide → act (settled)
npm run demo:dispute  # decide → act → prove (compensated)

Open-source projects

Agent infrastructure

  • Constitutional Agent Testbench: Deterministic Python policy evaluation and PrecedenceTrace for structured agent responses.

  • Consequence Rail: Recourse-gated execution, recovery preflight, and signed settlement receipts.

  • MandateBound: Evidence readiness and deterministic dispute replay for UCP/AP2 agentic commerce.

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

  • Agent Team: Bounded specialist-agent workflows with independent auditing.

Decision methods

  • Corridor Lab: Desktop GUI and CLI for comparing fictional cross-border payment routes across cost, speed, liquidity, and failure assumptions.
  • Unconventional Moves: Practical, non-obvious approaches with reversible 48-hour tests.

Experiments and examples

  • Hermes Parallel Follow-ups: Drop-in patches and regression tests that preserve message boundaries and route independent follow-ups while Hermes is busy.

How I build

Business problem → specification → implementation → adversarial evaluation → acceptance

Authorship

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

Pinned Loading

  1. consequence-rail consequence-rail Public

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

    JavaScript

  2. mandatebound mandatebound Public

    Evidence readiness and deterministic dispute replay for UCP/AP2 agentic commerce.

    TypeScript

  3. constitutional-agent-testbench constitutional-agent-testbench Public

    Deterministic policy evaluation and precedence tracing for structured agent responses.

    Python

  4. tracecanary tracecanary Public

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

    Python

  5. agent-team-os agent-team-os Public

    A reusable skill for bounded specialist workflows with independent auditing.

    Python

  6. agent-action-stack agent-action-stack Public

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

    JavaScript