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 Wenaixi/dsh-ponytail --skill ponytail-reviewgit clone --depth 1 https://github.com/Wenaixi/dsh-ponytailWrote 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/wenaixi/dsh-ponytail/ponytail-review)<a href="https://agentmods.dev/skills/wenaixi/dsh-ponytail/ponytail-review"><img src="https://agentmods.dev/badge/skills/wenaixi/dsh-ponytail/ponytail-review/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/wenaixi/dsh-ponytail/ponytail-review"><img src="https://agentmods.dev/badge/skills/wenaixi/dsh-ponytail/ponytail-review.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 | $0.00116 | $0.00658 |
| Opus 5 | $0.00058 | $0.00329 |
| Sonnet 5 | $0.00023 | $0.00132 |
| Haiku 4.5 | $0.00012 | $0.00066 |
Grade A, and why
ponytail-review 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.
What it actually says
只评审 diff 中的不必要复杂度，每条发现一行写完：位置、该删什么、用什么替代。diff 的最好结局是变短。
格式
L<行号>: <标签> <该删什么>。<替代方案>。 多文件 diff 用 <文件>:L<行号>: ...。
标签：
delete:死代码、未使用的灵活性、臆想功能。替代：无。stdlib:标准库已有的东西被手写了一遍，写出函数名。native:依赖或代码在做平台已有的事，写出平台特性名。yagni:只有一个实现的抽象、没人改的配置、只有一个调用方的分层。shrink:同样逻辑，更少行数，给出更短写法。
示例
❌ 「这个 EmailValidator 类是不是有点复杂，要不要考虑现阶段是否真的需要这么多校验规则？」
✅ L12-38: stdlib: 27 行的校验类。邮箱里有 "@" 就算 1 行，真正的校验是发确认邮件。
✅ L4: native: 为了一次格式化就引入 moment.js。用 Intl.DateTimeFormat，0 依赖。
✅ repo.py:L88: yagni: 只有一个实现的 AbstractRepository。先内联，等第二个实现出现再说。
✅ L52-71: delete: 在幂等的本地调用外包了一层重试。删掉即可。
✅ L30-44: shrink: 手写循环拼 dict。用 dict(zip(keys, values))，1 行。
评分
最后只留一个关心的指标：net: -<N> 行可删。
若无可删之处，直接说 已足够精简，直接发版。 并结束。
边界
范围：只看过度设计和复杂度。正确性 bug、安全漏洞、性能问题明确不在范围内，请走常规评审通道。单个冒烟测试或基于 assert 的自检是 ponytail 的最低要求，不算臃肿，永远不要标为可删。
只列发现，不直接改代码。
「stop ponytail-review / 正常模式」可切回啰嗦的评审风格。
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 · 46 lines · 116 tokens per session scan A c3559c885a81
ponytail-review is a skill published in the GitHub repository Wenaixi/dsh-ponytail (7 stars, last pushed 20d ago), licensed MIT. It adds 116 tokens to every session and 658 once invoked, about $0.0006 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
delivery-review
Adversarial self-review before delivery. Use once the implementation reaches green and before you declare the work done — assume the delivery fails its own spec, hunt for the strongest supportable objections, answer them, and re-review after fixes.
code2skill-review-source
A read-only review skill for checking whether a Code2Skill-generated result matches the source code it was authorized to use. It examines request handling, tool handoffs, transformations, authentication, and attachments.
code-review-zh
A Git-based code review workflow that compares changes from a chosen commit, branch, tag, or merge point. It checks both whether the code follows the repository's written standards and whether it implements the requested specification.
improve-codebase-architecture-zh
A codebase architecture review that scans for modules that hide useful complexity poorly, then produces a visual HTML report and discusses one selected finding in depth.
implement-zh
An implementation workflow for completing work described in a specification or tickets. It encourages test-first development where appropriate, runs checks during the work, and ends with review and a commit.
coding-standards
Baseline cross-project coding conventions for naming, readability, immutability, and code-quality review. Use detailed frontend or backend skills for framework-specific patterns. Use when reviewing code quality or naming with no framework-specific skill that applies.