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 Megaprompting/torque-loop --skill prompt-auditgit clone --depth 1 https://github.com/Megaprompting/torque-loopWrote 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/megaprompting/torque-loop/prompt-audit)<a href="https://agentmods.dev/skills/megaprompting/torque-loop/prompt-audit"><img src="https://agentmods.dev/badge/skills/megaprompting/torque-loop/prompt-audit/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/megaprompting/torque-loop/prompt-audit"><img src="https://agentmods.dev/badge/skills/megaprompting/torque-loop/prompt-audit.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 | $0.00084 | $0.00654 |
| Opus 5.5 | $0.00034 | $0.00262 |
| Sonnet 5.5 | $0.00017 | $0.00131 |
| Haiku 4.5 | $0.00008 | $0.00065 |
Grade A, and why
prompt-audit 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 2mo 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/ratchet:prompt-audit — the library as an OS
A prompt library is not a pile of good words; it is an operating system for cognition. This command audits it as one. It does not rewrite prompts first — it diagnoses the system: what work each prompt does, which moves are missing, and where the library lets the model escape into elegant analysis instead of producing something.
Step 0 — Load the library
Take the prompt list from the argument, a file, or the current context. Do not rewrite yet.
Classify
Tag each prompt by the type of work it performs (a prompt may do more than one):
- target locking · diagnosis · artifact production · adversarial testing · decision · patching · memory/state · orchestration · compression · boundary pushing
Find the system's shape
- Overrepresented moves — where the library is thick (usually diagnosis and "next move" prompts).
- Missing moves — where it is thin (usually artifact production, patching, testing, serialized state).
- Meta-looping prompts — those that ask what to ask next without ever forcing a move. These are the hallway of mirrors.
- Artifact-producing prompts — the ones that actually leave something behind.
- Prompts to delete or merge — redundant, vague, or low-consequence.
- The minimum new prompt set that would outperform the current library.
The operating rule
Judge every prompt against this bar. Keep it only if it does at least one:
- Forces a choice. 2. Creates an artifact. 3. Tests an artifact. 4. Patches a defect.
- Serializes useful state. 6. Kills a bad option. 7. Pushes to a higher-yield move.
Everything else is smoke.
Output contract
CLASSIFICATION: <table: prompt → work type(s)>
OVERREPRESENTED: <moves the library over-does>
MISSING: <moves it lacks — the expensive gaps>
META-LOOPERS: <prompts that never force a move>
DELETE / MERGE: <the cuts>
UPGRADED SET (sequenced workflow, not a pile):
1. <prompt> — <the move it forces>
2. ...
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.
- 2mo ago First seen · 66 lines · 84 tokens per session scan A 1c2a1abf87ba
prompt-audit is a skill published in the GitHub repository Megaprompting/torque-loop (10 stars, last pushed 8d ago), licensed MIT. It adds 84 tokens to every session and 654 once invoked, about $0.0003 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.
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