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Agent Skill · 研究检索

codedocs(codedocs 搜索)

codedocs 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

codedocs 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 35,158。

总安装 2,130周安装 87GitHub Stars 134下载 682核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:codedocs(codedocs 搜索)
来源仓库:https://github.com/absolutelyskilled/absolutelyskilled
仓库路径:skills/codedocs
安装命令:
npx skills add https://github.com/absolutelyskilled/absolutelyskilled --skill codedocs
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/absolutelyskilled/absolutelyskilled --skill codedocs

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

codedocs 用于生成结构化、分层的代码文档,专为 AI 代理优先消费而设计。适合在 Codex、Claude、Cursor、Gemini CLI 中为代码仓库创建可维护的文档体系时使用。生成 docs/ 目录树,包含架构概览、模块详细说明和交叉引用模式文件。

安装前建议确认项目规模和文档需求,注意会创建 manifest 跟踪文档状态。支持从文档回答问题而非重新分析源码,提高响应效率和准确性。

来源仓库内路径:skills/codedocs

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/absolutelyskilled/absolutelyskilled --skill co…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

codedocs 怎么安装?

在终端执行 npx skills add https://github.com/absolutelyskilled/absolutelyskilled --skill codedocs。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

codedocs 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

codedocs 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

codedocs 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

codedocs 用的人多吗?

公开数据是累计安装 2,130 次,近一周安装 87 次,下载 682 次,GitHub 134 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

codedocs 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
codedocs

codedocs 搜索 · 本页

2,130134需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

When this skill is activated, always start your first response with the 🧢 emoji.

Codedocs

Codedocs generates structured, layered documentation for any git repository or code directory - documentation designed to be consumed by AI agents first and human developers second. Instead of flat READMEs that lose context, codedocs produces a docs/ tree with an architecture overview, per-module deep dives, cross-cutting pattern files, and a manifest that tracks what has been documented and when. Once docs exist, the skill answers questions from the docs (not by re-reading source code), and supports incremental updates via targeted scope or git-diff detection.


Activation Banner

At the very start of every codedocs invocation, before any other output, display this ASCII art banner:

 ██████╗ ██████╗ ██████╗ ███████╗██████╗  ██████╗  ██████╗███████╗
██╔════╝██╔═══██╗██╔══██╗██╔════╝██╔══██╗██╔═══██╗██╔════╝██╔════╝
██║     ██║   ██║██║  ██║█████╗  ██║  ██║██║   ██║██║     ███████╗
██║     ██║   ██║██║  ██║██╔══╝  ██║  ██║██║   ██║██║     ╚════██║
╚██████╗╚██████╔╝██████╔╝███████╗██████╔╝╚██████╔╝╚██████╗███████║
 ╚═════╝ ╚═════╝ ╚═════╝ ╚══════╝╚═════╝  ╚═════╝  ╚═════╝╚══════╝

Follow the banner immediately with the active sub-command and target path, e.g.: codedocs:generate · src/ → docs/


When to use this skill

Trigger this skill when the user:

  • Wants to generate documentation for a codebase, repo, or directory
  • Asks "what does this project do" or "explain this codebase"
  • Needs onboarding docs for new team members joining a project
  • Wants AI-agent-readable documentation for a repo
  • Asks a question about a codebase that already has codedocs output
  • Needs to update existing docs after code changes or a new feature
  • Wants to document only a specific module or subdirectory
  • Asks to refresh docs based on recent git commits or a diff

Do NOT trigger this skill for:

  • Writing standalone technical documents (RFCs, ADRs, runbooks) - use internal-docs
  • API reference docs for external consumers - use technical-writing
  • README creation for open-source packaging - use open-source-management

Key principles

  1. Docs-first answers - Once codedocs output exists, always answer questions from the docs before falling back to source code. The docs are the cached, structured knowledge layer. Only read source code when docs are missing, stale, or insufficient for the specific question.
  2. Language-agnostic detection - Detect the tech stack from manifest files (package.json, Cargo.toml, go.mod, requirements.txt, pyproject.toml, composer.json, pom.xml, build.gradle, Gemfile, mix.exs, etc.) and directory conventions. Never assume a specific language.
  3. Modules map to code, patterns cut across - Module docs correspond to distinct code directories or bounded contexts (auth, api, database). Pattern docs capture cross-cutting concerns (error handling, testing strategy, logging conventions) that span multiple modules. This split prevents duplication and matches how developers think about code.
  4. Manifest-driven incremental updates - The .codedocs.json manifest tracks every documented module, its source path, and the git SHA at documentation time. Updates use this manifest to know what changed, what to re-scan, and what to skip.
  5. Output is configurable, structure is not - The output directory (default docs/) is configurable. The internal structure (OVERVIEW.md, INDEX.md,.codedocs.json, modules/, patterns/) is fixed. Consistency across repos means any agent or developer knows where to look.
  6. Coverage is a first-class metric - Documentation that covers 40% of a codebase is often worse than none - it gives a false sense of completeness. Always run coverage verification before presenting the plan. Target 70%+ for mid-size repos. Report coverage percentage in OVERVIEW.md and the manifest. See references/coverage-strategy.md for targets.
  7. Go deep, not just wide - For large repos, top-level modules are just the starting point. Any module with 15+ source files must be analyzed for sub-modules. Scan recursively through the full directory tree - a huge repo should generate 30-80 doc files, not 8-12.

Core concepts

Output structure - Codedocs always produces the same directory tree. OVERVIEW.md is the entry point covering architecture, tech stack, project structure tree, and module map. GETTING_STARTED.md is the authoritative local development guide with every runnable command in the repo. INDEX.md is the file-to-module lookup table. The modules/ directory contains one markdown file per major code module (with optional sub-module directories for large modules). The patterns/ directory contains cross-cutting concern docs. The .codedocs.json manifest tracks metadata, coverage stats, and SHAs for incremental updates. See references/output-structure.md for the full spec.

Four sub-commands - The skill exposes four operations: generate for full or scoped documentation creation, ask for docs-first Q&A, update for incremental refresh, and status for coverage reporting. Each has its own workflow and parameters. See the common tasks below and the corresponding reference files for detailed workflows.

Sub-modules - When a module directory has 15+ source files with distinct internal groupings, it is split into sub-modules. The parent module doc becomes an index; sub-module docs live at modules/<parent>/<child>.md. This keeps docs focused and prevents any single file from becoming an unreadably long catch-all.

Coverage verification - Before presenting the generation plan, codedocs computes what percentage of source files are covered by the proposed module set. If below target, it expands the scan to find additional modules. Coverage is tracked in the manifest and reported in OVERVIEW.md. See references/coverage-strategy.md.

Discovery phase - Before writing any docs, the generate command runs a discovery phase: scan the directory tree, identify the tech stack from manifest files, map module boundaries from directory structure and import graphs, and detect cross-cutting patterns from shared utilities and conventions. This phase produces the plan that drives doc generation.

Staleness detection - The update command compares the current git SHA against the SHA recorded in .codedocs.json for each module. Modules with changed files since last documentation are flagged as stale. The --diff flag uses git diff to identify exactly which files changed, enabling surgical updates to only the affected module docs.


Common tasks

1. Generate full codebase documentation

Command: codedocs:generate [path] [--output docs/]

Workflow:

  1. Discover - Scan the target path (default: repo root). Identify language/framework from manifest files. Map directory structure to candidate modules. Detect entry points (main files, index files, route definitions, CLI entry points).
  2. Plan - Present the user with a proposed doc plan: list of modules to document, patterns detected, estimated scope, and coverage percentage. Confirm before proceeding if the plan is large or ambiguous.
  3. Write OVERVIEW.md - Architecture summary, tech stack, annotated project structure tree, entry points, key concepts, and module map with one-line descriptions.
  4. Write GETTING_STARTED.md - Full local development guide: prerequisites, installation, environment setup, dev server, test commands, build commands, lint/format, database workflow, common dev tasks, and how to reproduce CI locally. Sourced from package.json scripts, Makefile targets, CI config, and any existing README setup sections.
  5. Write module docs - For each module: purpose, public API/exports, internal structure, dependencies (what it imports), dependents (what imports it), and key implementation notes.
  6. Write pattern docs - For each cross-cutting pattern: description, where it appears, conventions to follow, and examples from the codebase.
  7. Write manifest - Create .codedocs.json with module list, source paths, git SHA, generation timestamp, coverage stats, and config. See references/output-structure.md.

See references/generate-workflow.md for the complete discovery heuristics, module boundary detection logic, and OVERVIEW.md template.

2. Ask a question about the codebase

Command: codedocs:ask "<question>"

Workflow:

  1. Check for docs - Look for .codedocs.json in the output directory. If missing, suggest running codedocs:generate first.
  2. Route the question - Determine which doc file(s) are relevant. Architecture questions go to OVERVIEW.md. Module-specific questions go to the relevant module doc. Cross-cutting questions go to pattern docs.
  3. Read docs first - Load the relevant doc file(s) and attempt to answer from them.
  4. Fall back to source - If the docs don't contain enough detail, read the relevant source files. Flag in the response: "Note: this answer required reading source code - consider running codedocs:update to capture this in the docs."
  5. Cite sources - Always cite which doc file or source file the answer came from.

See references/ask-workflow.md for the question routing logic and fallback strategy.

3. Update docs incrementally (targeted scope)

Command: codedocs:update --scope path/to/module

Workflow:

  1. Read manifest - Load .codedocs.json to find the existing module mapping.
  2. Re-scan the scoped path - Run the discovery phase only on the specified path.
  3. Diff against existing docs - Compare the new discovery against the current module doc. Identify new exports, removed functions, changed dependencies.
  4. Update the module doc - Rewrite only the sections that changed.
  5. Update OVERVIEW.md - If the module's one-line description or dependency graph changed, update the module map in OVERVIEW.md.
  6. Update manifest - Bump the git SHA and timestamp for the updated module.

4. Update docs from git diff

Command: codedocs:update --diff [base..head]

Workflow:

  1. Get changed files - Run git diff --name-only base..head (default: last documented SHA from manifest to HEAD).
  2. Map files to modules - Using the manifest's source path mappings, determine which documented modules contain changed files.
  3. Re-generate affected modules - For each affected module, re-run the module doc generation workflow.
  4. Detect new modules - If changed files are in directories not yet documented, flag them as new module candidates and prompt the user.
  5. Update manifest - Bump SHAs for all updated modules.

See references/update-workflow.md for the diff detection logic and new module handling.

5. Generate docs for a specific subdirectory

Command: codedocs:generate path/to/subdir [--output path/to/subdir/docs/]

Same workflow as full generation but scoped to a subdirectory. The output defaults to a docs/ folder inside the specified path. Useful for monorepos where each package needs its own documentation.

6. Check documentation coverage

Command: codedocs:status

Workflow:

  1. Read manifest - Load .codedocs.json. If missing, suggest running codedocs:generate.
  2. Compute coverage - Count total source files in the repo vs files covered by documented modules.
  3. Detect staleness - For each module, compare the manifest SHA against the latest git commit SHA on that module's source path.
  4. Find gaps - List directories in the repo not covered by any module doc.
  5. Report - Print a structured status report: coverage percentage, stale modules, gap directories, and recommendations.

See references/coverage-strategy.md for coverage targets, the status report format, and strategies for improving coverage on large repos.


Anti-patterns / common mistakes

MistakeWhy it's wrongWhat to do instead
Re-reading source code when docs existWastes context window and time; docs are the structured cacheAlways check for .codedocs.json first; read docs before source
Documenting every file individuallyCreates noise; most files are internal implementation detailsDocument at the module level; only call out key files within a module
Skipping the discovery/plan phaseJumping straight to writing produces unstructured, incomplete docsAlways run discovery first; present the plan to the user for approval
Hardcoding language assumptionsBreaks on polyglot repos or unfamiliar stacksDetect from manifest files; handle multiple languages in one repo
Ignoring the manifest on updatesLeads to full re-generation when only one module changedAlways read .codedocs.json to scope updates to changed modules only
Mixing module docs and pattern docsCross-cutting concerns documented in one module become invisibleUse the patterns/ directory for anything that spans 2+ modules
Writing docs without git SHA trackingMakes incremental updates impossible; no way to know what's staleAlways populate the manifest with per-module git SHAs
Stopping at top-level directoriesA huge repo generates only 8-12 files; most of the codebase is invisibleRun the full recursive census (Step 3), verify coverage, and scan deeper
One flat doc for a 50-file moduleThe doc is too long to be useful; every question returns the same giant fileSplit modules with 15+ files into sub-modules (modules/<parent>/<child>.md)
Not checking coverage before presenting planLow-coverage plans look complete but leave most of the repo undocumentedAlways run Step 6 (coverage verification) before showing the plan
Skipping INDEX.mdAI agents can't map a specific file to its module docAlways generate INDEX.md as part of the output
Skipping GETTING_STARTED.mdDevelopers and agents can't run the project without hunting through package.json and READMEAlways generate GETTING_STARTED.md; source commands from scripts, Makefile, and CI config
Copying README verbatim into GETTING_STARTED.mdREADMEs are often incomplete or outdated; the guide adds no valueExtract commands from README but expand with context, fill gaps, and verify against actual scripts

Gotchas

  1. Manifest SHA drift causes phantom staleness - If the repo has uncommitted changes when codedocs:generate runs, the recorded git SHA doesn't match the working tree. Subsequent codedocs:update runs see all files as stale and attempt full re-generation. Run codedocs against a clean working tree or committed state where possible.
  2. Coverage counts source files, not lines - A large 2,000-line file and a small 50-line config file each count as one source file for coverage. A 70% coverage score can hide an undocumented core module if it happens to be split into many small files. Review the gap directory list in codedocs:status rather than trusting the percentage alone.
  3. Sub-module splitting creates orphaned parent docs - When a module with 15+ files is split into sub-modules, the parent modules/<name>.md should become an index pointing to sub-modules. If you create modules/api/routes.md and modules/api/middleware.md but leave the original modules/api.md intact unchanged, agents get conflicting information from two sources about the same code.
  4. Polyglot repos confuse module boundary detection - A repo with both a Python backend and a TypeScript frontend may have overlapping directory names (utils/, types/, config/) at different levels. The discovery phase can conflate these into one module. Explicitly verify module boundaries during the plan phase for monorepos or polyglot projects.
  5. GETTING_STARTED.md sourced only from README - READMEs are often incomplete or outdated. Commands listed in package.json scripts, Makefile targets, and CI config files frequently include critical developer workflows not mentioned in the README. Always cross-check all three sources when generating GETTING_STARTED.md.

References

For detailed workflows and schemas, read the relevant file from references/:

  • references/generate-workflow.md - Complete discovery heuristics, recursive census, multi-level module boundary detection, sub-module splitting, coverage verification, tech stack identification, and all output templates (OVERVIEW.md, module doc, pattern doc, INDEX.md). Load when running codedocs:generate.
  • references/ask-workflow.md - Question routing logic, doc-first resolution strategy, source code fallback rules, and citation format. Load when running codedocs:ask.
  • references/update-workflow.md - Diff detection logic, manifest-driven scoping, new module detection, and OVERVIEW.md sync rules. Load when running codedocs:update.
  • references/output-structure.md - Complete .codedocs.json manifest schema (v1.1 with coverage stats and sub-modules), directory layout spec including sub-module directories and INDEX.md, and file format guidelines. Load when creating or validating output.
  • references/coverage-strategy.md - Coverage targets by repo size, the codedocs:status report format, prioritization framework for large repos, and coverage improvement strategies. Load when running codedocs:status or when coverage is below target.

Only load a references file if the current task requires deep detail on that topic.


Companion check

On first activation of this skill in a conversation: check which companion skills are installed by running ls ~/.claude/skills/ ~/.agent/skills/ ~/.agents/skills/.claude/skills/.agent/skills/.agents/skills/ 2>/dev/null. Compare the results against the recommended_skills field in this file's frontmatter. For any that are missing, mention them once and offer to install: `` npx skills add AbsolutelySkilled/AbsolutelySkilled --skill <name> ` Skip entirely if recommended_skills` is empty or all companions are already installed.

平台分布

Codex

36.9%
按下载量换算252

Claude

30.33%
按下载量换算207

Cursor

19.51%
按下载量换算133

Gemini CLI

9.77%
按下载量换算67

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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