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 mixpanel/ai-plugins --skill review-documentgit clone --depth 1 https://github.com/mixpanel/ai-pluginsWrote 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/mixpanel/ai-plugins/review-document)<a href="https://agentmods.dev/skills/mixpanel/ai-plugins/review-document"><img src="https://agentmods.dev/badge/skills/mixpanel/ai-plugins/review-document/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/mixpanel/ai-plugins/review-document"><img src="https://agentmods.dev/badge/skills/mixpanel/ai-plugins/review-document.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 | $0.00158 | $0.01332 |
| Opus 5.5 | $0.00063 | $0.00533 |
| Sonnet 5.5 | $0.00032 | $0.00266 |
| Haiku 4.5 | $0.00016 | $0.00133 |
Grade A, and why
review-document 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 — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Documentation Review
Reviews a documentation set against a rubric and produces a percentage score plus a prioritised list of issues to fix. This is a read-only review — report, then offer a fix plan.
The first duty of docs is to be true: accuracy against the actual code is weighted highest and verified, not assumed. Beyond accuracy, docs must be current, concise, and navigable — every paragraph that restates the obvious competes with the one that carries the load. Score conservatively (see Scoring discipline).
Components
Rubric dimensions
The rubric evaluates 8 weighted dimensions. Read references/rubric.md for the full check definitions when running the evaluation.
| # | Dimension | Weight |
|---|---|---|
| 1 | Accuracy & Currency | 20% |
| 2 | Structure & Readability | 15% |
| 3 | Conciseness & DRY | 15% |
| 4 | Altitude & Scope | 10% |
| 5 | Completeness & Navigability | 10% |
| 6 | Clarity & Communication | 10% |
| 7 | Consistency & Conventions | 10% |
| 8 | Examples, Links & Commands | 10% |
Dimensions 3 and 4 carry the /simplify lens — duplication, filler, and wrong-altitude detail — applied to prose.
Scoring
Each check is scored PASS (1.0), WARN (0.5), FAIL (0.0), or N/A (excluded). All checks have equal weight within their dimension. See references/rubric.md for the full scoring formula and score caps.
| Score | Meaning |
|---|---|
| 95-100% | Accurate and polished — ready to publish |
| 85-94% | Minor issues — fix before publishing |
| 70-84% | Significant issues — needs rework |
| 50-69% | Major gaps or inaccuracy |
| 0-49% | Largely stale or misleading — rewrite |
Reviewer stance
The review must reflect a demanding reviewer, not a generous one. Adopt the stance of a seasoned editor or investigative journalist: assume the author is beside you and will push back, so go after the single weakest claim, not the average. Nothing earns praise by default; the doc earns each PASS.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 105 lines · 158 tokens per session scan A 4e65e354eeaa
review-document is a skill published in the GitHub repository mixpanel/ai-plugins (18 stars, last pushed 15d ago), licensed Apache-2.0. It adds 158 tokens to every session and 1,332 once invoked, about $0.0006 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 2026-08-30.
review-document compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| review-documentmixpanel/ai-plugins | Skill | 18 | 15d ago | Apache-2.0 | A | 158 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |