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Agent Skill · 研究检索

capture-learning(捕捉学习)

capture-learning 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 Codex、Claude、Cursor、Gemini CLI 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。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。

capture-learning 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,权限为接触敏感数据;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 52,586。

总安装 552周安装 23GitHub Stars 35下载 184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:capture-learning(捕捉学习)
来源仓库:https://github.com/petekp/claude-code-setup
仓库路径:skills/capture-learning
安装命令:
npx skills add https://github.com/petekp/claude-code-setup --skill capture-learning
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/petekp/claude-code-setup --skill capture-learning

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。

用于记录任务执行中的错误、纠正和经验缺口。适合让 Agent 持续沉淀问题、修正和最佳实践。可结合来源仓库和原始 README 核验具体用法。安装前建议确认权限范围和维护状态。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

capture-learning 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/capture-learning

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/petekp/claude-code-setup --skill capture-learn…;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

    它需要接触敏感数据,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

capture-learning 怎么安装?

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

capture-learning 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。

capture-learning 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

capture-learning 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。

capture-learning 用的人多吗?

公开数据是累计安装 552 次,近一周安装 23 次,下载 184 次,GitHub 35 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。

capture-learning 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

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 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

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
capture-learning

捕捉学习 · 本页

55235接触敏感数据未明确通过

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

Capture Learning

Analyze recent conversation context and capture learnings—either to project knowledge files or to skills/commands/subagents for cross-project reuse.

Core Workflow

Step 1: Analyze Recent Context

Review the current conversation to identify:

  1. Problem encountered - What went wrong or was confusing?
  2. Root cause - Why did it happen?
  3. Solution - How was it resolved?
  4. Prevention - How to avoid this in the future?

Extract concrete, actionable insights—not vague summaries.

Good learning:

When running `npm install` on Node 20+, the `--legacy-peer-deps` flag
is required due to React 18 peer dependency conflicts.

Bad learning:

Had some issues with npm install, fixed it eventually.

Step 2: Determine Learning Scope

Before deciding where to capture, ask: Is this learning project-specific or general?

ScopeCharacteristicsCapture Target
Project-specificInvolves this codebase's architecture, conventions, dependencies, or local setupProject knowledge files (.claude/CLAUDE.md, .claude/docs/)
GeneralApplies across all projects—language patterns, framework best practices, tool usage, API quirksSkills, commands, or subagents

Decision questions:

  1. Would this help in *other* projects using the same language/framework?
  2. Is this a general technique vs. this repo's specific implementation?
  3. Does an existing skill already cover this domain?

Examples:

LearningScopeTarget
"This repo uses ApiError class for error handling"Project-specific.claude/CLAUDE.md
"SwiftUI matchedGeometryEffect should only apply to background shapes, not content"Generalswiftui-excellence skill
"Run npm install --legacy-peer-deps for this project"Project-specific.claude/CLAUDE.md
"React Server Components can't use useState"Generalreact-component-dev skill or similar
"The CI pipeline requires NODE_ENV=test"Project-specific.claude/docs/setup.md
"Playwright's page.waitForSelector times out silently without proper error handling"Generalplaywright-qa-tester agent or new skill

If general: Navigate to the appropriate skill/command/subagent file and update it following its existing structure. Then confirm with user before saving.

If project-specific: Continue to Step 3.

Step 3: Scan for Knowledge Files (Project-Specific Learnings)

Detect existing knowledge files in the project's .claude/ directory:

# Primary targets (most common)
.claude/CLAUDE.md          # Main project instructions
./CLAUDE.md                # Root-level alternative

# Secondary targets
.claude/docs/*.md          # Reference documentation
.claude/docs/**/*.md       # Nested docs

# Tertiary (check but don't modify without explicit request)
.claude/plans/*.md         # Planning docs (usually ephemeral)

Priority order for updates:

  1. CLAUDE.md (project root or .claude/) - General learnings, setup issues
  2. .claude/docs/troubleshooting.md - If exists, for debugging insights
  3. .claude/docs/setup.md - If exists, for environment/build issues
  4. Create new file only if user requests it

Step 4: Categorize the Learning

Determine which section the learning belongs in:

Learning TypeTarget SectionExample
Build/dependency issues## Build & Setup or ## Troubleshootingnpm flags, version requirements
Environment setup## Environment or ## Prerequisitesenv vars, tool versions
Code patterns## Patterns or ## Conventionsnaming, architecture decisions
Known issues## Known Issues or ## Gotchasquirks, workarounds
Debugging insights## Debugginghow to diagnose specific problems

If the target section doesn't exist, propose creating it in a logical location.

Step 5: Draft the Update

Format the learning for documentation:

Structure for issue-based learnings:

### [Short descriptive title]

**Problem:** [What went wrong]
**Cause:** [Why it happened]
**Solution:** [How to fix/prevent]

Structure for pattern/convention learnings:

### [Pattern name]

[Brief description of when/why to use this pattern]

[Example if applicable]

Structure for quick tips:

- [Concise actionable tip]

Keep entries:

  • Scannable - Use headers, bullets, code blocks
  • Actionable - Provide concrete steps or commands
  • Contextual - Explain *why*, not just *what*

Step 6: Present Changes for Confirmation

Before modifying any file, show the user:

  1. Target file - Which file will be updated
  2. Location - Which section (existing or new)
  3. Proposed content - Exact text to be added
  4. Diff preview - Show context around insertion point

Example confirmation prompt:

I'll add this to `.claude/CLAUDE.md` under "## Troubleshooting":

### Node 20 Peer Dependency Fix

**Problem:** `npm install` fails with peer dependency conflicts
**Cause:** React 18 has strict peer deps incompatible with some packages
**Solution:** Run `npm install --legacy-peer-deps`

Should I apply this update?

Wait for explicit user approval before writing.

Step 7: Apply the Update

After confirmation:

  1. Read the target file
  2. Find the appropriate insertion point
  3. Add the new content with proper formatting
  4. Write the updated file
  5. Confirm the update was applied

If creating a new section, place it logically:

  • Setup/build sections near the top
  • Troubleshooting sections near the bottom
  • Patterns/conventions in the middle

File Detection Details

Scanning Strategy

# Check for .claude directory
ls -la .claude/ 2>/dev/null

# Find all markdown files in .claude
find .claude -name "*.md" -type f 2>/dev/null

# Check root for CLAUDE.md
ls CLAUDE.md 2>/dev/null

File Purpose Recognition

Infer file purpose from:

  1. Filename - troubleshooting.md, setup.md, patterns.md
  2. Location - .claude/docs/ for references, .claude/plans/ for planning
  3. Content - Existing section headers indicate file's scope
  4. CLAUDE.md special handling - Always a valid target for general learnings

When No Suitable File Exists

If .claude/CLAUDE.md doesn't exist:

  1. Check for ./CLAUDE.md in project root
  2. If neither exists, ask user:

- Create .claude/CLAUDE.md? - Create a specific doc file (e.g., .claude/docs/troubleshooting.md)? - Skip capturing this time?

Learning Extraction Patterns

Build/Setup Issues

Look for conversation patterns:

  • Error messages followed by resolution
  • "Fixed by..." or "The solution was..."
  • Version-specific workarounds
  • Missing dependencies or configuration

Extract: The error, root cause, and fix command/steps.

Code Patterns

Look for:

  • "This codebase uses..." discoveries
  • Architecture decisions explained
  • Naming conventions identified
  • Framework-specific patterns

Extract: Pattern description and rationale.

Debugging Insights

Look for:

  • Multi-step debugging processes
  • Non-obvious root causes
  • Diagnostic commands or techniques
  • "The issue was actually..."

Extract: Symptoms, investigation steps, root cause.

Examples

Example 1: Build Issue

Context: Session involved fixing a failing build due to TypeScript version mismatch.

Captured learning:

### TypeScript Version Requirement

**Problem:** Build fails with "Cannot find module 'typescript'"
**Cause:** Project requires TypeScript 5.3+ but system has 5.0
**Solution:**

npm install typescript@^5.3.0 --save-dev

Example 2: Environment Setup

Context: Session discovered required environment variables.

Captured learning:

### Required Environment Variables

The following must be set in `.env.local`:
- `DATABASE_URL` - PostgreSQL connection string
- `NEXTAUTH_SECRET` - Generate with `openssl rand -base64 32`
- `NEXTAUTH_URL` - Set to `http://localhost:3000` for development

Example 3: Code Pattern

Context: Session uncovered project's error handling convention.

Captured learning:

### Error Handling Pattern

All API routes use the `ApiError` class for consistent error responses:

throw new ApiError(404, "Resource not found");


The error handler middleware converts these to JSON responses.

Edge Cases

Multiple Learnings

If the session contains multiple distinct learnings:

  1. List them for the user
  2. Ask which to capture (or all)
  3. Process each separately with confirmation

Conflicting Information

If new learning contradicts existing documentation:

  1. Show both versions
  2. Ask user which is correct
  3. Update or replace as directed

Sensitive Information

Never capture:

  • API keys, tokens, or secrets
  • Passwords or credentials
  • Personal information
  • Internal URLs that shouldn't be documented

If a learning involves secrets, document the *pattern* without the actual values.

Quick Reference

Trigger phrases: "capture this", "remember this", "update docs", "document this", "add to CLAUDE.md", "save this knowledge"

First question: Is this project-specific or general?

Project-specific targets: .claude/CLAUDE.md (primary), .claude/docs/*.md (secondary)

General targets: Skills (~/.claude/skills/), commands (~/.claude/commands/), subagents (plugin agents)

Always confirm: Show exact changes before writing

Format: Problem → Cause → Solution (for issues), Description → Example (for patterns)

Additional Resources

Reference Files

  • references/section-templates.md - Complete templates for common documentation sections (Troubleshooting, Build & Setup, Environment, Patterns, Known Issues, Debugging). Consult when creating new sections or structuring complex learnings.

平台分布

Codex

35.43%
按下载量换算65

Claude

31.44%
按下载量换算58

Cursor

18.5%
按下载量换算34

Gemini CLI

9.5%
按下载量换算17

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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