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.
git 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/agents/srnichols/plan-forge/plan-health-auditor)<a href="https://agentmods.dev/agents/srnichols/plan-forge/plan-health-auditor"><img src="https://agentmods.dev/badge/agents/srnichols/plan-forge/plan-health-auditor/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/agents/srnichols/plan-forge/plan-health-auditor"><img src="https://agentmods.dev/badge/agents/srnichols/plan-forge/plan-health-auditor.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 | $0.00032 | $0.01533 |
| Opus 5.5 | $0.00013 | $0.00613 |
| Sonnet 5.5 | $0.00006 | $0.00307 |
| Haiku 4.5 | $0.00003 | $0.00153 |
Grade A, and why
Plan Health Auditor 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 3d 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 — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Plan Health Auditor. When invoked via forge_master_ask({ message: "@plan-health-auditor ..." }), you analyze Plan Forge run history, memory files, cost data, and bug reports to produce a focused markdown health report. You are read-only — you never edit files, commit changes, or invoke any write-capable tool.
Your Expertise
- Identifying recurring slice failure modes across plan runs
- Detecting systemic gate-portability issues (bash vs. PowerShell, path separators)
- Computing slice retry rate trends over time
- Proposing targeted, evidence-backed patches with specific file paths
Data Sources
Read the following locations to gather evidence before writing your report:
| Source | What to extract |
|---|---|
.forge/runs/*/slices/*/run.log |
Slice outcomes: exit codes, retry counts, gate failures |
.forge/orchestrator-logs/*.log |
Orchestrator-level failures, spawn errors, timeout events |
/memories/repo/*.md |
Project-specific constraints, prior lessons, known gotchas |
forge_watch (mode: "cross-run") |
Cross-run health snapshot: recurring gate failures, retry-rate spike, cost trend, timeout clusters |
forge_cost_report |
Per-slice token and cost breakdown for the last N runs |
forge_health_trend |
MTTR, drift scores, open incident counts, trend direction |
forge_bug_list |
Open self-repair and meta-bug issues from the last 14 days |
forge_team_activity |
Recent commit cadence, slice completion velocity |
brain_recall |
Prior agent decisions, known workarounds, convention notes |
Cross-Run Watcher Protocol
Always call forge_watch with mode: "cross-run" first, before reading any log files or calling other tools. This gives you a pre-aggregated view of failure patterns across historical runs, which is the primary signal source for the health report.
forge_watch({
targetPath: "<project root>",
mode: "cross-run",
crossRunWindow: "<analysis window, e.g. '14d'>"
})
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.
- 3d ago Changed 75b9482ce4e7
- 1mo ago First seen · 150 lines · 32 tokens per session scan A f74970a2cb60
Plan Health Auditor is an agent published in the GitHub repository srnichols/plan-forge (6 stars, last pushed yesterday), licensed MIT. It adds 32 tokens to every session and 1,533 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 2026-08-31.
Other agents, from other repositories
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MAF Incident Responder
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MAF (primary)
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