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 agentmods add skills/openinterpreter/openinterpreter/code-reviewnpx skills add openinterpreter/openinterpreter --skill code-reviewgit clone --depth 1 https://github.com/openinterpreter/openinterpreterWhat 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 | $0.00012 | $0.00135 |
| Opus 5 | $0.00006 | $0.00068 |
| Sonnet 5 | $0.00002 | $0.00027 |
| Haiku 4.5 | $0.00001 | $0.00014 |
Grade A, and why
code-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 2d 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
100% identical to code-review — 0 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
Use subagents to review code using all code-review-* skills other than this orchestrator. One subagent per skill. Pass full skill path to subagents. Use xhigh reasoning.
You must return every single issue from every subagent. You can return an unlimited number of findings. Use raw Markdown to report findings. Number findings for ease of reference. Each finding must include a specific file path and line number.
If the GitHub user running the review is the owner of the pull request add a code-reviewed label.
Do not leave GitHub comments unless explicitly asked.
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.
- 2d ago First seen · 15 lines · 12 tokens per session scan A 9446d3939a62
code-review is a skill published in the GitHub repository openinterpreter/openinterpreter (68,199 stars, last pushed 12d ago), licensed Apache-2.0. It adds 12 tokens to every session and 135 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to code-review, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
blog-writer
Peri 项目博客写作风格指南。当用户说"写博客"、"写文章"、"出稿"、 "按风格写"、"博客"时触发。也适用于用户丢过来素材说"帮我写篇博客"的场景。 覆盖项目介绍、技术复盘、架构讨论、性能优化、架构设计等类型。.
auto-devflow
Use when starting an issue, bugfix, feature, or refactor that benefits from an adaptive development workflow. Select lite, normal, pro, max, or ultra from task complexity and risk, then use only the coordination, review, and verification phases that the task actually needs.
langfuse
Interact with Langfuse and access its documentation. Use when needing to (1) query or modify Langfuse data programmatically via the CLI — traces, prompts, datasets, scores, sessions, and any other API resource, (2) look up Langfuse documentation, concepts, integration guides, or SDK usage, or (3) understand how any…
self-build
Builds isolated npm capability packages that operate on real project code and connects them to Peri through MCP/MCPP and MetaHarness. Use when adding tools, resources, remote skills or agents, creating a Bun/Node.js stdio server, linking .mcp.json, or changing the active prompt and middleware set.
project-maturity
对任意项目进行全面的成熟度评估扫描。当用户说"检查项目成熟度"、"项目评估"、 "maturity assessment"、"代码质量扫描"、"项目健康度"、"项目体检"、 "scan project maturity"、"项目有多成熟"时触发。适用场景：接手新项目前的摸底、 发布前的质量审查、技术尽调、团队内部代码健康度盘点。.
auto-issue-fixer
Issue 全生命周期管理——从创建到归档。当用户描述技术问题、提 bug、"帮我记录"、 "修一下 X issue"、"验证一下"、"归档 issue"时立即触发。单入口自动分发， 替代旧 issue-create/fix-issue/issue-verify/issue-archive 四个技能。 即使用户没有用"issue"这个词，只要在描述值得追踪的技术问题就应触发。.