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Agent Skill · 研究检索

analyze(分析)

analyze 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。

analyze 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,权限为执行命令;许可证为 MIT,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 55,572。

总安装 474周安装 19GitHub Stars 1下载 154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
MIT

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:analyze(分析)
来源仓库:https://github.com/jschulte/claude-plugins
仓库路径:skills/analyze
安装命令:
npx skills add https://github.com/jschulte/claude-plugins --skill analyze
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/jschulte/claude-plugins --skill analyze

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。

用于查找、检索和筛选相关信息。analyze 属于研究检索类 Skill,可作为该场景下的辅助能力补充。适合根据关键词或任务场景快速定位候选结果。可辅助研究类任务的信息收集环节。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。

建议结合具体需求验证搜索策略的有效性。需注意来源仓库的维护状态和实际功能边界。

来源仓库内路径:skills/analyze

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/jschulte/claude-plugins --skill analyze;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

    它需要执行命令,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

analyze 怎么安装?

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

analyze 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。

analyze 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/jschulte/claude-plugins --skill analyze;npx skills add jschulte/claude-plugins --skill "analyze" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

analyze 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

analyze 用的人多吗?

公开数据是累计安装 474 次,近一周安装 19 次,下载 154 次,GitHub 1 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。

analyze 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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

  • 不能接受 Skill 在你机器上执行命令的人。
  • 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
analyze

分析 · 本页

4741执行命令MIT有提醒

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

Initial Analysis (Gear 1 of 6)

Estimated Time: 5 minutes Output: analysis-report.md in the current working directory (always here, regardless of spec_output_location)


Activation Triggers

Activate this skill when the user says any of:

  • "Analyze this codebase"
  • "What tech stack is this using?"
  • "How complete is this application?"
  • "Run initial analysis"
  • "Start reverse engineering process"
  • Starting reverse engineering on a new or existing codebase

Execution Pipeline

This skill has four phases. Execute them in order.

Phase 0: Install Slash Commands

Run the commands in operations/install-commands.md to copy /speckit.* commands into the project.

If the copy command fails, log: "Slash command installation skipped -- commands can be installed later." Continue to Phase 1.

Log to user: "Phase 0 complete -- slash commands installed."

Phase 1: Detection

Check for Batch Session

Follow the procedure in operations/batch-session.md to search for .stackshift-batch-session.json.

If a batch session is found, load its answers, save them to .stackshift-state.json, skip Phase 2, and proceed to Phase 3.

If reading the batch session file fails, log the error and fall back to the normal questionnaire in Phase 2.

Log to user: "Phase 1 complete -- detection type: [type]."

Auto-Detect Application Type

Run these detection checks in priority order. Use the first match:

  1. monorepo-service: Parent directory is services/ or apps/ and ../../package.json exists
  2. nx-app: nx.json exists in current or grandparent directory
  3. turborepo-package: turbo.json exists in current or grandparent directory
  4. lerna-package: lerna.json exists in current or grandparent directory
  5. osiris: Repository name starts with ws-
  6. v9-velocity: widget.vm exists or path contains v9/widgets/
  7. v9-viewmodel: Path contains v9/viewmodel/widgets/
  8. generic: No specific pattern matched (default)

For detection types v9-velocity, v9-viewmodel, and osiris: these are legacy CMS widget types. Run the standard analysis phases (Phase 3) using generic analysis operations. Note in the report that this is a legacy CMS widget. If widget migration framework is selected in Phase 2, the /stackshift.widget-migrate command handles the specialized analysis.

Phase 2: Questionnaire

Present the questions defined in operations/questionnaire.md.

Ask questions conversationally, one at a time or in small related groups. Wait for the user to respond before continuing. Apply the conditional logic rules from that file to determine which questions to skip.

After collecting all answers, write them to .stackshift-state.json.

If .stackshift-state.json already exists, ask the user: "Existing configuration found. Reuse it or start fresh?"

Log to user: "Phase 2 complete -- configuration saved to.stackshift-state.json."

Phase 3: Analysis

Run all five analysis operations. For each operation, use the corresponding reference file. Run operations in parallel where possible.

  1. Detect tech stack -- operations/detect-stack.md Run all language detection commands in parallel. Missing files are normal. Log to user: "Analysis 1/5 complete -- tech stack detected."
  2. Extract core metadata -- Read application name, version, description from manifest files. Read git remote URL. Log to user: "Analysis 2/5 complete -- metadata extracted."
  3. Analyze directory structure -- operations/directory-analysis.md Map architecture patterns and key components. Log to user: "Analysis 3/5 complete -- directory structure analyzed."
  4. Scan documentation -- operations/documentation-scan.md Assess existing documentation quality. Log to user: "Analysis 4/5 complete -- documentation scanned."
  5. Assess completeness -- operations/completeness-assessment.md Estimate completion percentages with evidence. Log to user: "Analysis 5/5 complete -- completeness assessed."

Before proceeding to Phase 4, verify that all five operations produced results. If any operation produced no results, re-run it once. If it still fails, record "Unable to assess" for that section and continue.

Phase 4: Report Generation

Generate analysis-report.md using the template in operations/generate-report.md.

Write the report to the current working directory as analysis-report.md.

Read the StackShift version from .claude-plugin/plugin.json for the report header.

Log to user: "Phase 4 complete -- analysis-report.md generated."

Present a summary of findings to the user and ask if they are ready to proceed to Gear 2 (Reverse Engineer).


Path Descriptions

Greenfield (Build New App from Business Logic)

Use when building a new application based on existing business logic, migrating to a different tech stack, or wanting platform-agnostic specifications.

Result: Specifications focus on WHAT (business requirements only), tech-stack agnostic.

Example: "Extract the business logic from this Rails app so we can rebuild it in Next.js"

Brownfield (Manage Existing with Spec Kit)

Use when managing an existing codebase with specs, planning upgrades or refactoring, or needing specs that match current implementation.

Result: Specifications include WHAT and HOW (business logic + technical implementation), tech-stack prescriptive.

Example: "Add GitHub Spec Kit to this Next.js app so we can manage it with specs going forward"


Shell Command Error Handling

Apply these rules to every shell command across all operation files:

  1. Commands that return no output: Treat as "not found" and note the absence in the report. Do not treat as an error.
  2. Commands that fail with non-zero exit: Log the failure and continue with remaining commands. Never abort analysis due to a single command failure.
  3. Commands that produce excessive output: Use head -50 for directory listings and head -20 for grep results. Note truncation in the report if it occurs.
  4. Commands on files with spaces in names: Use -print0 / -0 flags with find/xargs pipelines where practical.
  5. Always exclude: node_modules, vendor,.git, build, dist, target, pycache,.next,.nuxt, coverage directories.

State Cleanup

If analysis fails or is interrupted before report generation, delete .stackshift-state.json to prevent stale configuration from affecting re-runs.

If the user cancels mid-analysis, inform them: "Analysis was interrupted. Run the analyze skill again to restart."


Cruise Control Behavior

When Cruise Control transmission is selected, the entire pipeline runs non-interactively after Phase 2. The progress log messages at each phase boundary serve as checkpoints. If any phase fails during Cruise Control, stop execution, report the failure, and ask the user how to proceed.


Handling Re-analysis

If analysis-report.md already exists when this skill activates:

  1. Ask the user: "An analysis report already exists. Update it, or skip to Gear 2?"
  2. If updating: re-run the full analysis pipeline and overwrite the existing report.
  3. If skipping: confirm the existing report is still accurate and proceed to Gear 2.

If the user already knows their tech stack and just wants to configure the pipeline, skip Phase 3 analysis operations and proceed directly to Phase 4 report generation using user-provided information.


After Analysis

Once analysis-report.md is generated and reviewed, proceed to Gear 2 (Reverse Engineer) using the reverse-engineer skill.

The analysis report is Gear 1's output. Gear 2 reads it as input to generate comprehensive documentation.

平台分布

Claude Code

28.62%
按下载量换算44

OpenCode

21.82%
按下载量换算34

Codex

15.96%
按下载量换算25

github-copilot

12.2%
按下载量换算19

Antigravity

6.68%
按下载量换算10

Gemini CLI

2.97%
按下载量换算5

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/jschulte/claude-plugins --skill analyze;npx skills add jschulte/claude-plugins --skill "analyze" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。

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