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Agent Skill · 研究检索

dependency(dependency 搜索)

dependency 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。

dependency 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,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 46,073。

总安装 808周安装 33GitHub Stars 6下载 261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:dependency(dependency 搜索)
来源仓库:https://github.com/duc01226/easyplatform
仓库路径:skills/dependency
安装命令:
npx skills add https://github.com/duc01226/easyplatform --skill dependency
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/duc01226/easyplatform --skill dependency

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。

用于查找和筛选与关键词或任务相关的信息。dependency 属于研究检索类 Skill,可作为该场景下的辅助能力补充。适用于 Codex、Claude、Cursor、Gemini CLI,支持 GitHub 安装。基于来源仓库和 README 提供候选结果,供进一步核验。

使用前应确认权限范围和维护状态,避免触发未授权操作。建议结合具体用例阅读原始文档以明确使用方式。

来源仓库内路径:skills/dependency

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/duc01226/easyplatform --skill dependency;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

dependency 怎么安装?

在终端执行 npx skills add https://github.com/duc01226/easyplatform --skill dependency。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

dependency 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。

dependency 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。

dependency 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。

dependency 用的人多吗?

公开数据是累计安装 808 次,近一周安装 33 次,下载 261 次,GitHub 6 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。

dependency 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。
  • 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。
  • 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

  • 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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 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
dependency

dependency 搜索 · 本页

8086需要联网MIT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

[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.
Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.
AI Mistake Prevention — Failure modes to avoid on every task: - Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal. - Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing. - Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain. - Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path. - When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site. - Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code. - Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks. - Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis. - Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly. - Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.

Prerequisites: MUST ATTENTION READ before executing:

Understand Code First — HARD-GATE: Do NOT write, plan, or fix until you READ existing code. 1. Search 3+ similar patterns (grep/glob) — cite file:line evidence 2. Read existing files in target area — understand structure, base classes, conventions 3. Run python.claude/scripts/code_graph trace <file> --direction both --json when .code-graph/graph.db exists 4. Map dependencies via connections or callers_of — know what depends on your target 5. Write investigation to .ai/workspace/analysis/ for non-trivial tasks (3+ files) 6. Re-read analysis file before implementing — never work from memory alone 7. NEVER invent new patterns when existing ones work — match exactly or document deviation BLOCKED until: - [] Read target files - [] Grep 3+ patterns - [] Graph trace (if graph.db exists) - [] Assumptions verified with evidence

Quick Summary

Goal: Analyze and visualize dependencies between features, services, or work items to identify blockers and critical paths.

Workflow:

  1. Identify Scope — Single feature, module, or full release
  2. Classify Dependencies — Data, Service, UI, or Infrastructure types
  3. Build Graph — Create Mermaid dependency diagram
  4. Find Critical Path — Longest blocking chain; mark ready-to-start items
  5. Deliver Report — Summary, graph, critical path, risks

Key Rules:

  • Respect microservice boundaries (cross-service = message bus only)
  • Flag circular dependencies as errors
  • Not for package/npm upgrades (use package-upgrade instead)

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Dependency Mapping

Purpose

Analyze and visualize dependencies between features, services, modules, or work items to identify blockers, critical paths, and safe execution order.

When to Use

  • Planning feature implementation sequence across modules
  • Identifying what blocks a specific feature or work item
  • Mapping cross-service dependencies (backend-to-backend, frontend-to-backend)
  • Understanding critical path for a release or milestone
  • Analyzing impact of changing a shared module or entity

When NOT to Use

  • Single-service code changes with no cross-boundary impact -- just implement directly
  • Performance analysis -- use arch-performance-optimization instead
  • Security dependency auditing -- use arch-security-review instead
  • Package/npm dependency upgrades -- use package-upgrade instead

Prerequisites

  • Read the feature/PBI/plan files to understand scope
  • Access to docs/project-reference/project-structure-reference.md for service boundary reference
  • Understand the project's microservice boundaries (search src/Services/ for service list)

Workflow

Step 1: Identify Scope

Determine what to map:

  • Single feature: Find all files, services, and entities it touches
  • Module/service: Map all inbound and outbound dependencies
  • Release/milestone: Map all features and their inter-dependencies

Step 2: Classify Dependencies

For each dependency found, classify by type:

TypeDirectionDescriptionExample
DataEntity A requires Entity BForeign key, navigation property, shared IDEmployee requires Company
ServiceService A calls Service BMessage bus, API call, event consumerService A consumes entity events from Service B
UIComponent A embeds Component BShared component, library dependencyFeature form uses shared component library select
InfrastructureFeature needs infra changeDatabase migration, config, new queueNew feature needs Redis cache key

Step 3: Build Dependency Graph

Use Mermaid syntax for visualization:

graph TD
    A[Feature A] -->|data| B[Feature B]
    A -->|service| C[Feature C]
    B -->|blocks| D[Feature D]
    C -->|blocks| D
    style D fill:#f96,stroke:#333

Step 4: Identify Critical Path

  • Find the longest chain of blocking dependencies
  • Mark items with no blockers as "ready to start"
  • Flag circular dependencies as errors

Step 5: Deliver Report

Output structured dependency report (see Output Format).

Output Format

## Dependency Map: [Feature/Module Name]

### Summary

- Total items: N
- Ready to start: N (no blockers)
- Blocked: N
- Critical path length: N steps

### Dependency Graph

[Mermaid diagram]

### Critical Path

1. [Item A] -- no blockers, estimated: Xd
2. [Item B] -- blocked by: A, estimated: Xd
3. [Item C] -- blocked by: B, estimated: Xd

### Dependency Details

| Item | Type                  | Depends On | Blocks | Status        |
| ---- | --------------------- | ---------- | ------ | ------------- |
| ...  | data/service/UI/infra | ...        | ...    | ready/blocked |

### Risks

- [Circular dependency / tight coupling / single point of failure]

Examples

Example 1: Backend Cross-Service Feature

Input: "Map dependencies for adding a new Coaching feature in {ServiceA}"

Analysis:

graph TD
    E[Employee Entity - ServiceA] -->|data| C[Coaching Entity]
    U[User Entity - AuthService] -->|service| C
    C -->|service| N[Notification - ServiceB]
    C -->|UI| CF[Coaching Form Component]
    CF -->|UI| BC[shared-components select]

Critical path: Employee Entity -> Coaching Entity -> Coaching API -> Coaching Form Ready to start: Employee Entity already exists, shared component select exists Blocked: Coaching Entity creation, then API, then UI

Example 2: Frontend Module Dependency

Input: "What blocks the new Dashboard widget in {AnalyticsService}?"

Analysis:

graph TD
    GA[Source API - ServiceA] -->|service| GE[Event Bus Message]
    GE -->|service| GC[Consumer - AnalyticsService]
    GC -->|data| GS[Summary Entity]
    GS -->|UI| GW[Dashboard Widget]
    GW -->|UI| DC[Dashboard Container]

Blockers identified:

  1. Event Bus Message producer must exist in ServiceA (exists: yes)
  2. Consumer must be created in AnalyticsService (exists: no -- BLOCKER)
  3. Summary Entity for aggregated data (exists: no -- BLOCKER)

Related Skills

  • project-manager -- for sprint planning and status tracking
  • feature-implementation -- for implementing features after dependency analysis
  • arch-cross-service-integration -- for designing cross-service communication
  • package-upgrade -- for npm/NuGet package dependency upgrades

Closing Reminders

  • MANDATORY IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting
  • MANDATORY IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code
  • MANDATORY IMPORTANT MUST ATTENTION cite file:line evidence for every claim (confidence >80% to act)
  • MANDATORY IMPORTANT MUST ATTENTION add a final review todo task to verify work quality MANDATORY IMPORTANT MUST ATTENTION READ the following files before starting:
  • MANDATORY IMPORTANT MUST ATTENTION search 3+ existing patterns and read code BEFORE any modification. Run graph trace when graph.db exists.
  • MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.
  • MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using TaskCreate.

平台分布

Claude Code

28.12%
按下载量换算73

windsurf

23.27%
按下载量换算61

OpenCode

15.39%
按下载量换算40

Codex

11.48%
按下载量换算30

Antigravity

7.31%
按下载量换算19

Gemini CLI

3.39%
按下载量换算9

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。

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