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 bacnh85/pi-extensions --skill ponytail-auditgit clone --depth 1 https://github.com/bacnh85/pi-extensionsWrote 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/bacnh85/pi-extensions/ponytail-audit)<a href="https://agentmods.dev/skills/bacnh85/pi-extensions/ponytail-audit"><img src="https://agentmods.dev/badge/skills/bacnh85/pi-extensions/ponytail-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/bacnh85/pi-extensions/ponytail-audit"><img src="https://agentmods.dev/badge/skills/bacnh85/pi-extensions/ponytail-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 | $0.00107 | $0.00404 |
| Opus 5 | $0.00053 | $0.00202 |
| Sonnet 5 | $0.00021 | $0.00081 |
| Haiku 4.5 | $0.00011 | $0.00040 |
Grade A, and why
ponytail-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 9d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 9d ago First seen · 42 lines · 107 tokens per session scan A ebfed6e7ac83
ponytail-audit is a skill published in the GitHub repository bacnh85/pi-extensions (17 stars, last pushed yesterday), with no licence file. It adds 107 tokens to every session and 404 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 2026-08-31.
Other skills, from other repositories
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security-review
Security review of the diff — the third review axis alongside Standards and Spec. Reviews for injection, auth, secrets, deserialization, SSRF, path traversal, unsafe operations, and dependency confusion. Use as a parallel sub-agent with fresh context (diff-only, anti-anchored) during the review phase.
code-review
Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes: Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/spec asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use…
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Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
receiving-code-review
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation.
code-review
Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes — Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/spec asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use…