agentleFS
OyadotAIOyadotAI/oya-browser/.agents/skills/code-review/SKILL.md

code-review

Skill351 starsChanged 11 days agoLicence not identifiedView on GitHub

This skill should be used when reviewing a branch, pull request, working tree, or changes since a commit for repository standards and the user's requested behavior.

We split this skill into the rules it gives an agent

2 rules. 0 are common, 1 is distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 185 edited versions we read keep these.

  • 1

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

The licence could not be identified — read it at the source. We count its rules but don't quote them. Read them on GitHub.

“Common” is measured: kept by at least 6 in 10 of the 185 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

  • Other versions195 projects use a version of this.

    Word for word · 0

    None found.

    Edited · 0

    None found.

    Wrote their own version · 195

    1. mattpocock/skills★ 303ksame name
    2. TheAlgorithms/Python★ 226ksame name
    3. microsoft/vscode★ 194ksame name
    4. github/spec-kit★ 145ksame name
    5. ggml-org/llama.cpp★ 132ksame name
    6. shareAI-lab/analysis_claude_code★ 78ksame name
    7. shareAI-lab/learn-claude-code★ 78ksame name
    8. vectorize-io/hindsight★ 54ksame name
    9. dbeaver/dbeaver★ 52ksame name
    10. roboflow/supervision★ 51ksame name

    185 more not listed

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • Used alongsideProjects with it also use add-new-model, azsdk-common-sdk-breaking-change and 10 more.

    Other files people use alongside this one.

    Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
    • PydanticSkill

      add-new-model

      Add support for a newly-released language or image generation model in pydantic-ai (e.g. openai:gpt-5.6, anthropic:claude-sonnet-5, openai:gpt-image-2). Use when a provider ships a new model id and you need to wire literals, profile flags, adapters, and tests to recognize it. Handles SDK-lag, gateway list conventions, capability probing, and direct image-model geometry.

      Also in 9 projects that use this

    • Microsoft AzureSkill

      azsdk-common-sdk-breaking-change

      Detect and mitigate SDK Breaking changes for an SDK package which is generated from TypeSpec. WHEN: "Detect SDK breaking changes for a service", "Detect SDK breaking changes for an SDK package", "Detect and mitigate SDK breaking changes for a service", "Detect and mitigate SDK breaking changes for an SDK package". INVOKES: skill: azsdk-common-generate-sdk-locally; MCP tools: azure-sdk-mcp:azsdk_customized_code_update, azure-sdk-mcp:azsdk_package_detect_breaking_change.

      Also in 4 projects that use this

    • dzhngSkill

      audit-choices

      Audit the choices an implementing agent made, not its diff — a pure decision audit that traces the session's history into a choices ledger, changes no code, and never blocks an unsupervised run. Working code still embeds architecture the user never chose; surface it because future work inherits it. Use when the user wants to review the decisions the AI made on their behalf, before merging or committing AI-implemented work, when integrating a delegated subagent's pass, or when a fix "works" but might be a point fix.

      Also in 4 projects that use this

    • ww-w-aiSkill

      bkend-auth

      bkend.ai authentication guide. Signup, login, JWT tokens, sessions, role-based access control, and password management with bkend.ai BaaS. Triggers: bkend auth, bkend login, bkend signup, JWT, session, RBAC, password, bkend 인증, 로그인, 회원가입, bkend認証, ログイン, 新規登録, bkend认证, 登录, 注册, autenticacion bkend, authentification bkend, bkend-Auth Do NOT use for: data operations (use $bkend-data), file storage (use $bkend-storage).

      Also in 4 projects that use this

    • ww-w-aiSkill

      bkend-cookbook

      bkend.ai cookbook with step-by-step tutorials and example projects. Build a todo app, blog, e-commerce store, and more with bkend.ai BaaS. Triggers: bkend cookbook, bkend tutorial, bkend example, todo app, blog app, bkend 쿡북, bkend 튜토리얼, 예제 프로젝트, bkendクックブック, チュートリアル, bkend教程, 示例项目, tutorial bkend, tutoriel bkend, bkend-Tutorial, ricettario Do NOT use for: initial setup (use $bkend-quickstart), specific features (use $bkend-data/auth/storage).

      Also in 4 projects that use this

    • dzhngSkill

      close-spec

      When a spec under specs/<feature>/ is done shipping (a write-spec build, or any planned task that produced a spec), archive it to specs/done/ and rewrite it from a build-plan into a durable rationale — the why, the principles, the invariants — pointing back to the real code for the how. Use when implementation has landed and the plan no longer matches what shipped, or the user says a feature/spec is finished. Pairs with [write-spec](../write-spec/SKILL.md) (the plan this closes) and [review](../review/SKILL.md) (run before closing).

      Also in 4 projects that use this

    • +5 more from ww-w-ai
    • +1 more from dzhng
  • In this repository25 other files it gives its agents.

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What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

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