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/diegomarino/fable-auditsWrote 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/commands/diegomarino/fable-audits/fix)<a href="https://agentmods.dev/commands/diegomarino/fable-audits/fix"><img src="https://agentmods.dev/badge/commands/diegomarino/fable-audits/fix/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/commands/diegomarino/fable-audits/fix"><img src="https://agentmods.dev/badge/commands/diegomarino/fable-audits/fix.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 | $0.00020 | $0.01170 |
| Opus 5.5 | $0.00008 | $0.00468 |
| Sonnet 5.5 | $0.00004 | $0.00234 |
| Haiku 4.5 | $0.00002 | $0.00117 |
Grade A, and why
fix scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Execute fixes from an adversarial-audit report or fixes backlog, finding by finding, exactly as specified below. The invocation should name the target report under docs/audits/ and optionally an ID list or severity floor; if it doesn't -- an empty or literal unexpanded "$ARGUMENTS" counts as not named -- list the reports in docs/audits/, including those nested in - run directories, and ask which one before touching anything.
Control-plane boundary
This spec governs only the task it defines. A newer human instruction or higher-priority runtime policy overrides this spec. STOP ends autonomous work under this spec; it never prevents the agent from honoring that control plane.
Role
Staff engineer executing another reviewer's findings. Skeptical: an audit captures a snapshot and code moves -- re-verify before you fix. Conservative: a fixing agent that guesses at design intent causes more damage than the defect it fixes. No change without a reproduced defect and a passing acceptance check.
Ground rules
- When the target report has a .findings.json sidecar, treat it as the canonical finding list; the markdown report supplies the human context.
- Fix in severity order unless the invocation names specific IDs.
- One finding at a time; keep every change attributable to its ID.
- When the backlog marks several IDs as one root cause, fix the root cause once and record all covered IDs.
- Match repo conventions (style, error handling, test idioms) -- read neighboring code first.
- Never silence the alarm to stop the ringing: no skipping failing tests, deleting assertions, loosening validation, or catch-and-ignore to make a symptom disappear.
- Stay inside the finding's blast radius: no drive-by refactors.
- Git: leave all changes uncommitted; never commit, push, stash, or otherwise touch git state. Maintainer owns git.
Command safety
Mutate only the working tree and local throwaway state. Do not run destructive, publishing, deploy, migration, credential-mutating, network-writing, or external-service-mutating commands -- acceptance checks included: if a finding's recorded acceptance check requires one, mark the finding BLOCKED and state the exact command you would have run.
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.
- 1mo ago First seen · 55 lines · 20 tokens per session scan A 89058baa0d72
fix is a command published in the GitHub repository diegomarino/fable-audits (2 stars, last pushed 2mo ago), licensed MIT. It adds 20 tokens to every session and 1,170 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 commands, from other repositories
ccc-debug-session
Run a structured debug session: gather context, rank hypotheses, test them without editing code, then fix with a regression test and record the lesson. Use when a bug's cause is unclear.
scan
A codebase onboarding briefing that examines a new project's files, tools, main entry points, and marked technical debt.
perf
Structured performance investigation with baselines, profiling, and evidence-backed decisions.
bifrost-debug
Diagnose why the Bifrost gateway, memory injection, or skill discovery isn't working.
bug-fix
Streamlines bug fixing by creating a GitHub issue first, then a feature branch for implementing and thoroughly testing the solution before merging.
parallax-status
Summarize the current session and run package/native lifecycle diagnostics.