Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add jleechanorg/agent-orchestrator-ts --skill tdd-evidence-workflowgit clone --depth 1 https://github.com/jleechanorg/agent-orchestrator-tsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jleechanorg/agent-orchestrator-ts/tdd-evidence-workflow)<a href="https://agentmods.dev/skills/jleechanorg/agent-orchestrator-ts/tdd-evidence-workflow"><img src="https://agentmods.dev/badge/skills/jleechanorg/agent-orchestrator-ts/tdd-evidence-workflow/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jleechanorg/agent-orchestrator-ts/tdd-evidence-workflow"><img src="https://agentmods.dev/badge/skills/jleechanorg/agent-orchestrator-ts/tdd-evidence-workflow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00023 | $0.00693 |
| Opus 5.5 | $0.00009 | $0.00277 |
| Sonnet 5.5 | $0.00005 | $0.00139 |
| Haiku 4.5 | $0.00002 | $0.00069 |
Grade A, and why
tdd-evidence-workflow scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TDD-Driven Evidence Workflow (Evidence-Driven Development)
This skill operationalizes Test-Driven Development (TDD) as the primary mechanism for generating authentic, authoritative evidence for pull requests.
Core Principle: No Evidence without Proving the Failure
Authentication of a fix requires proving that the bug or gap existed immediately before the fix was applied. This is achieved by capturing the "Red" phase of TDD.
The Workflow
All AO workers and agents MUST follow these steps for every bug fix or feature implementation:
1. Identify and Reproduce (The "Red" Phase)
- Action: Write a new test case (unit, integration, or E2E) that fails due to the missing feature or existing bug.
- Evidence Capture: Run this test and capture the failure.
- For Terminal work: Capture the fenced log output showing the failure (e.g.,
AssertionError). - For UI/Interactive work: Capture a video (.mp4/.gif/.cast) showing the failing interaction.
- For Terminal work: Capture the fenced log output showing the failure (e.g.,
- Artifact: Label this as
initial_failureorred_phasein your evidence bundle.
2. Implement and Verify (The "Green" Phase)
- Action: Implement the minimal code changes required to make the test pass.
- Evidence Capture: Run the same test again and capture the success.
- For Terminal work: Capture the fenced log output showing
PASS. - For UI/Interactive work: Capture a video (.mp4/.gif/.cast) showing the successful interaction.
- For Terminal work: Capture the fenced log output showing
- Artifact: Label this as
final_verificationorgreen_phasein your evidence bundle.
3. Refactor and Finalize
- Action: Clean up the code, ensure it adheres to style guidelines, and run the full test suite.
- Evidence Capture: Final test results for the entire component.
Mandatory Evidence Structure
Your ## Evidence section in the PR MUST include both phases:
## Evidence
### TDD Cycle Proof
- **Initial Failure (Red)**: [repro_failure.log](URL) or [repro_video.mp4](URL)
- **Final Verification (Green)**: [verify_success.log](URL) or [verify_video.mp4](URL)
### Summary
| Phase | Result | Artifact |
|-------|--------|----------|
| Red | FAIL | logs/initial.log |
| Green | PASS | logs/final.log |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 63 lines · 23 tokens per session scan A 44e22bb44ec7
tdd-evidence-workflow is a skill published in the GitHub repository jleechanorg/agent-orchestrator-ts (8 stars, last pushed 3d ago), licensed MIT. It adds 23 tokens to every session and 693 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-02.
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