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Audit Trail — measured AI agent skill | DecimalAI

a5c-ai/audit-trail

SkillScore59Maintained

Full traceability from PRD to code commit through the CCPM spec-driven pipeline.

by a5c-ai

Links this skill to your agents and keeps it current with the author’s updates.

Automatic

Project Management pack

decimalai skills pull a5c-ai-audit-trail

Get this skill — curl · raw file

curl -fsSL https://app.decimal.ai/s/a5c-ai-audit-trail/SKILL.md

Raw file: /s/a5c-ai-audit-trail/SKILL.md ↗ · machine-readable summary at /s/a5c-ai-audit-trail.json ↗

In productionGlobal

how this skill behaves on real traffic · last 30 days

No production data for this skill yet — usage numbers appear here once agents start running it.

Anonymized aggregate across every org using this skill — proof from real production use, not a demo.

Does this skill help? · Benchmark: with vs. withoutsign in to run this on your agents

22 test cases from the publisher’s eval.yaml · each run twice on gemini-3.6-flash — with the skill injected, then without · last run 9d ago

Yes — +59% lift-37% tokens0% turns59% of whole cases pass with skill (13/22)

Test case	Without → With	Effect	Δ tokens	Δ turns
case-02	✗→✓	▲ Improved	-28%	0%
case-04	✗→✓	▲ Improved	1%	0%
case-05	✗→✓	▲ Improved	-62%	0%
case-06	✗→✓	▲ Improved	-75%	0%
case-07	✗→✓	▲ Improved	-58%	0%

Showing 5 of 22 cases

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 7/31/2026

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

a5c-ai / babysitter

library/methodologies/ccpm/skills/audit-trail/SKILL.md

View on GitHub ↗

License MITImported 7/31/2026Version v1

Skill contents

SKILL.md

Audit Trail

Full traceability from PRD to code commit through the CCPM spec-driven pipeline.

Traceability Chain

PRD -> Epic -> Task -> GitHub Issue -> Code Commit

Capabilities

PRD user story to task mapping
Task to GitHub issue linking
Commit to issue cross-referencing
Coverage matrix generation
Audit completeness verification

File Structure

.claude/
  prds/<feature-name>.md          # PRD with user stories
  epics/<feature-name>/
    epic.md                        # Technical epic
    1.md, 2.md, ...               # Individual tasks
    tasks-index.md                # Task index with traceability

Audit Verification

The tracking process (ccpm-tracking.js) verifies:

Every PRD user story maps to at least one task
Every task maps to a GitHub issue (if sync enabled)
Every completed task has associated commits
Coverage percentage is reported

Want to see if a5c-ai/audit-trail would activate on your phrasing? Try it before you install — no LLM call, no signup.

Other measured skills in the registry, with their headline benchmark lift.