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/mturac/promptguardWrote 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/mturac/promptguard/prompt-audit)<a href="https://agentmods.dev/commands/mturac/promptguard/prompt-audit"><img src="https://agentmods.dev/badge/commands/mturac/promptguard/prompt-audit.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 5.1 | $0.00010 | $0.00047 |
| Opus 5 | $0.00005 | $0.00023 |
| Sonnet 5 | $0.00002 | $0.00009 |
| Haiku 4.5 | $0.00001 | $0.00005 |
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 8d 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.
What it actually says
Audit the prompt target in $ARGUMENTS using PromptGuard.
Report: Severity | Evidence | Impact | Missing/Conflicting Contract | Fix Draft.
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.
- 8d ago First seen · 8 lines · 10 tokens per session scan A 16ab9ea4666a
prompt-audit is a command published in the GitHub repository mturac/promptguard (85 stars, last pushed 1mo ago), licensed MIT. It adds 10 tokens to every session and 47 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
prompt
A command that creates AI prompts and applies fixed rules for constraints, principles, and when the command may run.
prompt-sync
A command that synchronizes a prompt-generation system with a local folder, a personal vault, and a deployment repository. It keeps the same source structure across those locations.
prompt-update
A command for updating and combining prompt-engineering guidance, meaning methods for writing clearer instructions for AI.
auto-prompt
A command for automatically generating AI prompts in a format compatible with K-AI Station. The available description does not specify which prompt tasks or models it supports.
prompt-review
Scan prompts for ground rule, KISS/DRY, AI sweep, and context budget violations.
prompt-optimize
Apply fixes for issues found by prompt-review.