Borrowing it
Nothing to install: this file belongs to ouranos-labs/pseolint. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ouranos-labs/pseolint/main/.claude/skills/ponytail-audit/SKILL.mdgit clone --depth 1 https://github.com/ouranos-labs/pseolintWrote 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/ouranos-labs/pseolint/ponytail-audit)<a href="https://agentmods.dev/skills/ouranos-labs/pseolint/ponytail-audit"><img src="https://agentmods.dev/badge/skills/ouranos-labs/pseolint/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/ouranos-labs/pseolint/ponytail-audit"><img src="https://agentmods.dev/badge/skills/ouranos-labs/pseolint/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 | $0.00105 | $0.00389 |
| Opus 5 | $0.00053 | $0.00195 |
| Sonnet 5 | $0.00021 | $0.00078 |
| Haiku 4.5 | $0.00011 | $0.00039 |
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 12d 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.
This is a copy
89% identical to ponytail-audit — 5 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
ponytail-review, repo-wide. Scan the whole tree instead of a diff. Rank findings biggest cut first.
Tags
Same as ponytail-review:
delete:dead code, unused flexibility, speculative feature. Replacement: nothing.stdlib:hand-rolled thing the standard library ships. Name the function.native:dependency or code doing what the platform already does. Name the feature.yagni:abstraction with one implementation, config nobody sets, layer with one caller.shrink:same logic, fewer lines. Show the shorter form.
Hunt
Deps the stdlib or platform already ships, single-implementation interfaces, factories with one product, wrappers that only delegate, files exporting one thing, dead flags and config, hand-rolled stdlib.
Output
One line per finding, ranked: <tag> <what to cut>. <replacement>. [path].
End with net: -<N> lines, -<M> deps possible. Nothing to cut: Lean already. Ship.
Boundaries
Complexity only, correctness bugs, security holes, and performance go to a normal review pass. Lists findings, applies nothing. One-shot. "stop ponytail-audit" or "normal mode" to revert.
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.
- 12d ago First seen · 41 lines · 105 tokens per session scan A c0f03b6e1d95
ponytail-audit is a skill published in the GitHub repository ouranos-labs/pseolint (6 stars, last pushed 2d ago), licensed MIT. It adds 105 tokens to every session and 389 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to ponytail-audit, differing in 5 lines, and is treated as a copy.
Other skills, from other repositories
updater
Check Claude Code changelog for lintable changes and implement cclint updates. Use when a new Claude Code version ships, when CLAUDE.md claudecodelastupdated is stale, or for version gap detection, domain classification, and parallel agent dispatch across CUE schemas, hook events, known tools, and lint rules.
next-application-structure
Establishes or reviews directory layout, server/client boundaries, routing, data-fetching strategy, and testing structure for Next.js 14+ App Router TypeScript applications. Invoked when the user asks to structure a Next app, set App Router conventions, or review architecture for React parity.
ruff-docs
Ruff — fast Python linter and formatter in Rust. 900+ rules, Black-compatible formatter, LSP, CI/CD.
quorum:audit
Run a quorum audit manually — trigger consensus review, re-run failed audits, test audit prompts, or force a specific provider. Use when the hook-based auto-trigger didn't fire, or you want explicit control.
quorum:tools
Run any of the 20 quorum analysis tools — codebase, quality, domain checks, RTM/FVM, and audit history. Use whenever you need code analysis or domain checks.
karpathy-guidelines
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.