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Agent Skill · 研究检索

feature-investigation(特征调查)

feature-investigation 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。

feature-investigation 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;许可证为 MIT,暂无第三方扫描结果,按安装量在研究检索类的 73,675 个 Skill 里排第 47,223。

总安装 744周安装 31GitHub Stars 公开资料未说明下载 248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:feature-investigation(特征调查)
来源仓库:https://github.com/duc01226/easyplatform
仓库路径:skills/feature-investigation
安装命令:
npx skills add duc01226/easyplatform --skill "feature-investigation"
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。

AgentSkills.tonpx skills
npx skills add duc01226/easyplatform --skill "feature-investigation"

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。

feature-investigation 用于查找、检索和筛选相关信息,支持特征调查分析。适用于需求调研和竞品分析等研究场景。使用 npx skills add duc01226/easyplatform --skill "feature-investigation" 安装。

需确认调研目标和数据源可靠性,注意隐私保护和合规要求。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。

来源仓库内路径:skills/feature-investigation

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 duc01226/easyplatform --skill "feature-investigation";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

feature-investigation 怎么安装?

在终端执行 npx skills add duc01226/easyplatform --skill "feature-investigation"。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

feature-investigation 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。

feature-investigation 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。

feature-investigation 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。

feature-investigation 用的人多吗?

公开数据是累计安装 744 次,近一周安装 31 次,下载 248 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。

feature-investigation 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

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。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 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

  • 要求有安全扫描结论才肯安装的团队。
  • 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
feature-investigation

特征调查 · 本页

744—需要联网MIT未收录

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

Skill Variant: Use this skill for investigating and understanding existing features or logic. This is a READ-ONLY exploration skill - no code changes. For implementing new features, use feature-implementation. For debugging, use debugging.

Feature Investigation & Logic Exploration

You are to operate as an expert full-stack dotnet angular principal developer and software architect to investigate and explain how an existing feature or logic works in [feature-description-or-question].

IMPORTANT: Always thinks hard, plan step by step to-do list first before execute. Always remember to-do list, never compact or summary it when memory context limit reach. Always preserve and carry your to-do list through every operation. Todo list must cover all phases, from start to end, include child tasks in each phases too, everything is flatted out into a long detailed todo list.

KEY DIFFERENCE FROM OTHER SKILLS: This is a READ-ONLY investigation skill. You are NOT implementing or fixing anything - you are building understanding and explaining how things work.


Core Anti-Hallucination Protocols

ASSUMPTION_VALIDATION_CHECKPOINT

Before every major operation:

  1. "What assumptions am I making about [X]?"
  2. "Have I verified this with actual code evidence?"
  3. "Could I be wrong about [specific pattern/relationship]?"

EVIDENCE_CHAIN_VALIDATION

Before claiming any relationship:

  • "I believe X calls Y because..." → show actual code
  • "This follows pattern Z because..." → cite specific examples
  • "Service A owns B because..." → grep for actual boundaries

TOOL_EFFICIENCY_PROTOCOL

  • Batch multiple Grep searches into single calls with OR patterns
  • Use parallel Read operations for related files
  • Combine semantic searches with related keywords

CONTEXT_ANCHOR_SYSTEM

Every 10 operations:

  1. Re-read the original question from the ## Metadata section
  2. Verify the current operation aligns with answering the question
  3. Check if we're investigating the right thing
  4. Update the Current Focus bullet point within the ## Progress section

Quick Reference Checklist

Before any major operation:

  • ASSUMPTION_VALIDATION_CHECKPOINT
  • EVIDENCE_CHAIN_VALIDATION
  • TOOL_EFFICIENCY_PROTOCOL

Every 10 operations:

  • CONTEXT_ANCHOR_CHECK
  • Update 'Current Focus' in ## Progress section

Emergency:

  • Context Drift → Re-read ## Metadata section
  • Assumption Creep → Halt, validate with code
  • Evidence Gap → Mark as "inferred"

PHASE 1: EXTERNAL MEMORY-DRIVEN FEATURE INVESTIGATION

Your sole objective is to build a structured knowledge model in a Markdown analysis file at .ai/workspace/analysis/[feature-name]-investigation.md with systematic external memory management.

PHASE 1A: INITIALIZATION AND DISCOVERY

  1. Initialize the analysis file with:

- ## Metadata heading with original question in markdown box - ## Investigation Question - clearly state what we're trying to understand - Create headings: ## Progress, ## Assumptions, ## File List, ## Knowledge Graph, ## Data Flow, ## Findings

  1. Populate ## Progress with:

- Phase: 1 - Items Processed: 0 - Total Items: 0 - Current Operation: "initialization" - Current Focus: "[original investigation question]"

  1. Discovery searches to find all related files:

- Semantic search and grep search all keywords from the question - Prioritize: Domain Entities, Commands, Queries, Event Handlers, Controllers, Background Jobs, Consumers, Components - Additional targeted searches: - .*EventHandler.*{FeatureName}|{FeatureName}.*EventHandler - .*BackgroundJob.*{FeatureName}|{FeatureName}.*BackgroundJob - .*Consumer.*{FeatureName}|{FeatureName}.*Consumer - .*Service.*{FeatureName}|{FeatureName}.*Service - .*Component.*{FeatureName}|{FeatureName}.*Component - Save ALL file paths to ## File List

PHASE 1B: KNOWLEDGE GRAPH CONSTRUCTION

IMPORTANT: MUST DO WITH TODO LIST

  1. Count total files, split into batches of 10 files in priority order
  2. Insert batch analysis tasks into todo list

For each file, document in ## Knowledge Graph:

  • filePath: Full path
  • type: Component classification
  • architecturalPattern: Design pattern used
  • content: Purpose and logic summary
  • symbols: Classes, interfaces, methods
  • dependencies: Imports/using statements
  • businessContext: Business logic contribution
  • referenceFiles: Files using this file's symbols
  • relevanceScore: 1-10 (to the investigation question)
  • evidenceLevel: "verified" or "inferred"
  • platformAbstractions: Platform base classes
  • serviceContext: Microservice ownership

Investigation-Specific Fields:

  • entryPoints: How this code is triggered/called
  • outputPoints: What this code produces/returns
  • dataTransformations: How data is modified
  • externalDependencies: External services, APIs, databases accessed
  • configurationDependencies: Config values, feature flags, settings
  • conditionalLogic: Key decision points and branches
  • errorScenarios: What can go wrong, error handling

For Consumers/Message Bus:

  • messageBusMessage: Message type consumed
  • messageBusProducers: Who sends this message (grep across all services)
  • crossServiceIntegration: Cross-service data flow

MANDATORY: After every 10 files, update Items Processed and run CONTEXT_ANCHOR_CHECK.

PHASE 1C: DATA FLOW MAPPING

Under ## Data Flow, document:

  1. Entry Points: Where the feature begins (API endpoint, UI action, scheduled job, message)
  2. Processing Pipeline: Step-by-step flow through the code
  3. Data Transformations: How data changes at each step
  4. Persistence Points: Where data is saved/loaded
  5. Exit Points: Final outputs (responses, events, side effects)
  6. Cross-Service Flows: If data crosses service boundaries

Create a text-based flow diagram:

[Entry] → [Step 1] → [Step 2] → [Step 3] → [Exit]
              ↓           ↓
         [Side Effect] [Database]

PHASE 2: COMPREHENSIVE ANALYSIS

PHASE 2A: WORKFLOW ANALYSIS

Document under ## Workflow Analysis:

  1. Happy Path: Normal successful execution flow
  2. Error Paths: How errors are handled at each stage
  3. Edge Cases: Special conditions and their handling
  4. Authorization: Permission checks and security gates
  5. Validation: Input validation at each layer

PHASE 2B: ARCHITECTURAL ANALYSIS

Document under ## Architectural Analysis:

  1. Layers Involved: Domain, Application, Infrastructure, Presentation
  2. Patterns Used: CQRS, Repository, Event Sourcing, etc.
  3. Service Boundaries: Which microservices are involved
  4. Integration Points: External systems, message bus, APIs
  5. State Management: Frontend state patterns (stores, signals)

PHASE 2C: BUSINESS LOGIC EXTRACTION

Document under ## Business Logic:

  1. Core Business Rules: What rules govern this feature
  2. Validation Rules: Input/data validation
  3. Calculations: Any computations performed
  4. State Transitions: Entity state changes
  5. Side Effects: Notifications, events, external calls

PHASE 3: FINDINGS SYNTHESIS

PHASE 3A: EXECUTIVE SUMMARY

Write a clear, concise answer to the original question under ## Executive Summary:

  • One-paragraph answer to the user's question
  • Key files involved (top 5-10 most important)
  • Key patterns used

PHASE 3B: DETAILED EXPLANATION

Under ## Detailed Explanation:

  1. Step-by-step walkthrough of how the feature works
  2. Code references with file:line for each step
  3. Why it works this way - architectural decisions

PHASE 3C: VISUAL REPRESENTATION

Under ## Diagrams:

  1. Sequence Diagram (text-based) showing component interactions
  2. Data Flow Diagram showing data transformations
  3. Component Diagram showing file relationships
┌─────────────┐     ┌─────────────┐     ┌─────────────┐
│  Component  │────>│   Command   │────>│   Handler   │
└─────────────┘     └─────────────┘     └─────────────┘
                                               │
                                               v
                                        ┌─────────────┐
                                        │ Repository  │
                                        └─────────────┘

PHASE 3D: RELATED DISCOVERIES

Under ## Related Discoveries:

  • Connected Features: Other features that interact with this one
  • Shared Components: Reusable code discovered
  • Potential Issues: Any concerns or technical debt noticed
  • Documentation Gaps: Missing or outdated documentation

PHASE 4: PRESENTATION

Present your findings to the user in a clear, organized format:

  1. Start with the answer - directly address their question
  2. Provide evidence - show the code that supports your answer
  3. Explain the flow - walk through the logic step by step
  4. Offer deeper dives - mention areas you can explain further

Response Format

## Answer

[Direct answer to the question in 1-2 paragraphs]

## How It Works

### 1. [First Step]

[Explanation with code reference at `file:line`]

### 2. [Second Step]

[Explanation with code reference at `file:line`]

...

## Key Files

| File                  | Purpose   |
| --------------------- | --------- |
| `path/to/file.cs:123` | [Purpose] |

## Data Flow

[Text diagram showing the flow]

## Want to Know More?

I can explain further:

- [Topic 1]
- [Topic 2]
- [Topic 3]

Investigation Guidelines

  • Evidence-based investigation: Every claim must have code evidence
  • Service boundary awareness: Understand which service owns what
  • Platform pattern recognition: Identify Easy.Platform patterns used
  • Cross-service tracing: Follow message bus flows across services
  • Read-only exploration: Never suggest changes unless asked
  • Question-focused: Always tie findings back to the original question
  • Layered explanation: Start simple, offer deeper detail if requested

Common Investigation Scenarios

"How does feature X work?"

  1. Find entry points (API, UI, job)
  2. Trace through command/query handlers
  3. Document entity changes
  4. Map side effects (events, notifications)

"Where is the logic for Y?"

  1. Search for keywords in commands, queries, entities
  2. Check event handlers for side effect logic
  3. Look in helper/service classes
  4. Check frontend stores and components

"What happens when Z occurs?"

  1. Identify the trigger (user action, event, schedule)
  2. Trace the handler chain
  3. Document all side effects
  4. Map error handling

"Why does A behave like B?"

  1. Find the relevant code path
  2. Identify decision points
  3. Check configuration/feature flags
  4. Document business rules

Platform-Specific Investigation Patterns

Backend Patterns to Look For

  • PlatformCqrsCommand / PlatformCqrsQuery - CQRS entry points
  • PlatformCqrsEntityEventApplicationHandler - Side effects
  • PlatformApplicationMessageBusConsumer - Cross-service consumers
  • IPlatformQueryableRootRepository / IPlatformQueryableRootRepository - Data access
  • PlatformValidationResult - Validation logic
  • [PlatformAuthorize] - Authorization

Frontend Patterns to Look For

  • AppBaseVmStoreComponent - State management components
  • PlatformVmStore - Store implementations
  • effectSimple / tapResponse - Effect handling
  • observerLoadingErrorState - Loading/error states
  • API services extending PlatformApiService

See Also

  • feature-implementation skill - For implementing new features (code changes)
  • debugging skill - For debugging and fixing issues (use --autonomous for structured workflow)
  • tasks-feature-implementation skill - Autonomous feature implementation variant
  • .ai/prompts/context.md - Platform patterns and context
  • CLAUDE.md - Codebase instructions

Task Planning Notes

  • Always plan and break many small todo tasks
  • Always add a final review todo task to review the works done at the end to find any fix or enhancement needed

平台分布

Claude Code

26.58%
按下载量换算66

windsurf

26.29%
按下载量换算65

OpenCode

19.04%
按下载量换算47

Codex

11.8%
按下载量换算29

Antigravity

7.8%
按下载量换算19

Gemini CLI

3.24%
按下载量换算8

安全审计

暂无安全审计结果可展示。

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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