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Agent Skill · 研究检索

re-structure-analysis(重组分析)

re-structure-analysis 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。

re-structure-analysis 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,权限为调用外部服务;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 59,803。

总安装 376周安装 16GitHub Stars 公开资料未说明下载 132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:re-structure-analysis(重组分析)
来源仓库:https://github.com/caldiaworks/caldiaworks-marketplace
仓库路径:skills/re-structure-analysis
安装命令:
npx skills add https://github.com/caldiaworks/caldiaworks-marketplace --skill re-structure-analysis
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/caldiaworks/caldiaworks-marketplace --skill re-structure-analysis

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。

re-structure-analysis 用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词或任务场景快速定位候选结果。通过 npx skills add 命令从指定仓库安装,需结合原始 README 确认具体用法。

安装前建议确认权限范围、维护状态及是否触发联网、命令执行或文件读写操作。该技能适用于需要重新组织分析结构或优化信息架构的场景。

来源仓库内路径:skills/re-structure-analysis

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/caldiaworks/caldiaworks-marketplace --skill re…;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

    它需要调用外部服务,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

re-structure-analysis 怎么安装?

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

re-structure-analysis 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。

re-structure-analysis 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

re-structure-analysis 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。

re-structure-analysis 用的人多吗?

公开数据是累计安装 376 次,近一周安装 16 次,下载 132 次。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。

re-structure-analysis 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
re-structure-analysis

重组分析 · 本页

376—调用外部服务未明确通过

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

Structure Analysis — Reverse Engineering Phase 1

Analyze the target codebase structure exhaustively. Identify ALL entry points, dependencies, modules, and components within the user-specified scope. Produce a structure map document and initialize manifest.json for pipeline chaining.

Three Principles

These principles are non-negotiable. Violating any principle invalidates the analysis.

1. Code is Truth

  • Document what IS implemented, not what SHOULD be implemented
  • If code appears buggy, document the behavior as-is and note it in the Question List
  • Prioritize actual code over comments, variable names, or documentation

2. Traceability to Line

  • Every finding MUST include a file:line reference
  • If a line number cannot be determined, exclude the finding and note it in the Question List
  • References without line numbers are considered hallucination

3. Behavior over Intent

  • Focus on observable behavior: inputs, outputs, side effects
  • Do NOT infer business intent or "why" from code
  • Document "what" and "how" only

Execution

Step 1: Setup

Determine analysis name:

  • Use the name argument if provided
  • Otherwise derive from target: class name, directory name, or file stem

Detect language:

  • If language argument is provided, use it
  • Otherwise detect from file extensions and project files:

- .cs / *.csproj → csharp - .py / pyproject.toml / setup.py → python - .ts / .tsx / package.json with typescript → typescript - .java / pom.xml / build.gradle → java - Other → generic

Load language reference:

  • Check if references/{language}.md exists in this skill's directory
  • If it exists, read and apply the language-specific patterns
  • If not, proceed with language-agnostic analysis

Detect tool availability:

  • Check if Serena MCP tools are available (mcp__serena__find_symbol, etc.)
  • If available, use Serena as primary analysis tools
  • If not, use Read, Grep, Glob, Bash exclusively

Create output directory and manifest:

mkdir -p docs/reverse/{name}
mkdir -p docs/reverse/{name}/verification

Initialize manifest.json:

{
  "name": "{name}",
  "language": "{detected-language}",
  "created": "{YYYY-MM-DD}",
  "updated": "{YYYY-MM-DD}",
  "targets": {
    "entry_points": ["{user-specified targets}"],
    "classes": ["{extracted class names}"],
    "specified_by": "user"
  },
  "phase1": {
    "status": "in_progress",
    "output": null,
    "verification": null,
    "targets_for_phase2": []
  },
  "phase2": {
    "status": "pending",
    "completed": [],
    "remaining": [],
    "targets_for_phase3": []
  },
  "phase3": {
    "status": "pending",
    "completed": [],
    "remaining": []
  },
  "phase4": {
    "status": "pending",
    "output": null,
    "verification": null
  }
}

Step 2: Entry Point Detection

Identify all entry points within the target scope.

With Serena:

mcp__serena__get_symbols_overview(relative_path="{target}", depth=1)
mcp__serena__find_symbol(name_path_pattern="Main|main|__main__|app")

Without Serena:

  • Use Grep to search for entry point patterns from the language reference
  • Use Read to examine candidate files
  • Use Glob to find project configuration files

For each entry point, record:

  • File path (relative to workspace root)
  • Line number
  • Function/method name
  • Purpose (derived from code, not inferred)

Step 3: Dependency Mapping

Identify dependencies within the target scope.

Package/library dependencies:

  • Read project configuration files (language-specific: *.csproj, pyproject.toml, package.json, pom.xml)
  • List external dependencies with versions

Internal module dependencies:

  • Trace imports/using statements from the target files
  • Build a dependency graph

Produce Mermaid diagram:

graph TD
    ModuleA --> ModuleB
    ModuleA --> ExternalLib
    ModuleB --> ModuleC

Mermaid syntax rules (prevent parse errors):

  • No special characters in text (!=, >=, [], ())
  • No array/generic syntax (byte[], List<string> → byte array, string list)
  • No method call parentheses (Method() → Method)
  • Use quotes for node text with spaces: A["Node text (L45)"]

Step 4: Module and Component Listing

List ALL classes, interfaces, functions, and significant components within the target scope.

With Serena:

mcp__serena__search_for_pattern(
    substring_pattern="class |interface |def |function ",
    restrict_search_to_code_files=true
)
mcp__serena__get_symbols_overview(relative_path="{directory}", depth=2)

Without Serena:

  • Use Grep to find class/function definitions
  • Use Read to examine each file
  • Use Glob to enumerate source files

For each component, record:

ComponentTypeFile:LineDescription
OrderServiceclasssrc/services/order.py:15Order processing service

CRITICAL: List ALL components. Selecting only "important" ones is prohibited. Partial listing invalidates the analysis for downstream phases.

Step 5: Build Phase 2 Target List

From the component list, identify classes/modules that contain methods requiring logic visualization:

  • Classes with business logic methods
  • Handlers/controllers with processing flows
  • Services with complex operations

For each, record:

{
  "class": "OrderService",
  "file": "src/services/order.py",
  "methods": ["process_order", "validate_order", "calculate_total"]
}

Step 6: Generate Output

Write structure map to docs/reverse/{name}/01-structure-map.md:

# Structure Map: {name}

**Analysis Date**: {YYYY-MM-DD}
**Target**: {relative path}
**Language**: {language}
**Framework**: {detected framework and version}
**Confidence**: {High / Medium / Low}

**Important**: All paths are relative to workspace root.

## Technology Stack

### Framework and Language
| Component | Version | Source |
|:----------|:--------|:-------|
| {language} | {version} | {file:line} |

### Dependencies
| Package | Version | Purpose | Source |
|:--------|:--------|:--------|:-------|
| {package} | {version} | {purpose} | {config-file:line} |

## Directory Tree

{tree output with functional annotations}

## Entry Points

| Entry Point | File:Line | Purpose | Evidence |
|:------------|:----------|:--------|:---------|
| {name} | [{file}:{line}]({file}:{line}) | {purpose} | Line {N} |

## Dependency Diagram

graph TD ...


## Module and Component List

### {Category} (e.g., Services, Handlers, Models)

| Component | Type | File:Line | Description |
| --- | --- | --- | --- |
| {name} | {class/interface/function} | [{file}:{line}](https://github.com/caldiaworks/caldiaworks-marketplace/blob/HEAD/skills/re-structure-analysis/%7Bfile%7D:%7Bline%7D) | {description} |

## Question List

### Unconfirmed Findings

- **[Unconfirmed]** {description} — [{file}:{line}](https://github.com/caldiaworks/caldiaworks-marketplace/blob/HEAD/skills/re-structure-analysis/%7Bfile%7D:%7Bline%7D)

### Suspected Issues

- **[Suspected Bug]** {description} — [{file}:{line}](https://github.com/caldiaworks/caldiaworks-marketplace/blob/HEAD/skills/re-structure-analysis/%7Bfile%7D:%7Bline%7D)

## Analysis Constraints

### Confidence Factors

- **Code comments**: {sparse/moderate/rich}
- **Test coverage**: {estimated %}
- **Architecture patterns**: {observed patterns}

### Evidence Strength

- ✅ **Strong**: Implementation + tests + clear behavior
- ⚠️ **Medium**: Implementation + partial tests
- ❌ **Weak**: Implementation only, inferred from structure

Update manifest:

  • Set phase1.status to "completed"
  • Set phase1.output to "01-structure-map.md"
  • Populate phase1.targets_for_phase2 with the Phase 2 target list
  • Update phase2.remaining with all component names from targets_for_phase2
  • Update updated timestamp

Validation Before Completion

Before writing output, verify:

  • [ ] Every finding has a file:line reference
  • [ ] No speculative content (all claims verifiable in source)
  • [ ] Mermaid diagrams use valid syntax (no special characters)
  • [ ] All file paths are relative to workspace root
  • [ ] Component list is exhaustive within target scope
  • [ ] manifest.json is valid JSON with all required fields
  • [ ] targets_for_phase2 contains entries for all components with analyzable methods

Prohibited Actions

  • Do NOT execute code or run build commands
  • Do NOT infer business logic from variable names alone
  • Do NOT add components not present in the source code
  • Do NOT modify any source files
  • Do NOT include absolute file paths in output

平台分布

Codex

37.62%
按下载量换算50

Claude

28.6%
按下载量换算38

Cursor

18.69%
按下载量换算25

Gemini CLI

9.18%
按下载量换算12

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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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