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 agentmods add skills/srnichols/plan-forge/audit-loopnpx skills add srnichols/plan-forge --skill audit-loopgit clone --depth 1 https://github.com/srnichols/plan-forgeWrote 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/srnichols/plan-forge/audit-loop)<a href="https://agentmods.dev/skills/srnichols/plan-forge/audit-loop"><img src="https://agentmods.dev/badge/skills/srnichols/plan-forge/audit-loop.svg" alt="Measured on agentmods" 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 | $0.00100 | $0.00876 |
| Opus 5 | $0.00050 | $0.00438 |
| Sonnet 5 | $0.00020 | $0.00175 |
| Haiku 4.5 | $0.00010 | $0.00088 |
Grade A, and why
audit-loop 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 yesterday.
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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Audit Loop Skill
Trigger
"Run an audit loop" / "Drain findings" / "Audit my app" / "Find bugs in the running system" / "Recursive audit"
Steps
1. Start the Drain Loop
Call the forge_tempering_drain MCP tool to run a multi-round tempering drain. The drain discovers findings from the running system, applies the classifier, and repeats until convergence (zero real findings) or the round cap is hit.
Pass through any user-supplied options:
maxRounds— cap on iterations (default 5)env— target environment (defaultdev)dryRun— if true, discover findings but skip triage side effects
Review the drain result for:
- Number of rounds executed
- Per-round finding counts (the drain curve)
- Whether the loop converged or hit the round cap
- The final set of unresolved findings
2. Triage Each Finding
For every finding returned by the drain, call the forge_triage_route MCP tool to classify it into one of three lanes:
| Lane | Meaning | Next Action |
|---|---|---|
| bug | Real product defect | File via forge_bug_register |
| spec | Feature or spec gap | Route to plan pipeline |
| classifier | Noise / false positive | Propose classifier PR |
Collect triage results and group by lane.
3. Report the Drain Curve
Present a summary showing the drain trajectory and triage breakdown:
Audit Loop Results:
Rounds: N executed (converged: yes/no)
Drain curve: R1: 12 → R2: 5 → R3: 1 → R4: 0
Triage:
🐛 Bug: N findings → filed / ready to file
📋 Spec: N findings → routed to plan pipeline
🔇 Classifier: N findings → classifier PR proposed
Overall: CONVERGED at round N / HIT CAP at round N
Safety Rules
- Default environment is
dev— never target production unless explicitly requested --dry-runskips all side effects (bug filing, spec routing, classifier PRs)- Respect
audit.modein.forge.json— if set tooff, warn the user and stop - This skill orchestrates existing tools; it does NOT crawl or classify directly
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.
- yesterday First seen · 79 lines · 100 tokens per session scan A ba77f9b682de
audit-loop is a skill published in the GitHub repository srnichols/plan-forge (5 stars, last pushed 2d ago), licensed MIT. It adds 100 tokens to every session and 876 once invoked, about $0.0005 per session on Opus 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 2026-09-03.
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