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Agent Skill · 研究检索

task-decomposition(任务分解)

task-decomposition 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。

task-decomposition 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,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 12,812。

总安装 9,949周安装 423GitHub Stars 69下载 3,486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:task-decomposition(任务分解)
来源仓库:https://github.com/jwynia/agent-skills
仓库路径:skills/task-decomposition
安装命令:
npx skills add https://github.com/jwynia/agent-skills --skill task-decomposition
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/jwynia/agent-skills --skill task-decomposition

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。

task-decomposition 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。适用于根据关键词、任务场景或来源线索进行信息筛选。通过 npx skills add 命令从 GitHub 仓库安装并使用。

安装前需确认权限范围、维护状态及是否触发联网或文件操作。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/task-decomposition

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/jwynia/agent-skills --skill task-decomposition;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

task-decomposition 怎么安装?

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

task-decomposition 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。

task-decomposition 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/jwynia/agent-skills --skill task-decomposition;npx skills add jwynia/agent-skills --skill "task-decomposition" 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。

task-decomposition 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。

task-decomposition 用的人多吗?

公开数据是累计安装 9,949 次,近一周安装 423 次,下载 3,486 次,GitHub 69 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。

task-decomposition 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

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 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

  • 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
task-decomposition

任务分解 · 本页

9,94969执行命令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

Task Decomposition Diagnostic

Transform overwhelming development tasks into manageable units by respecting cognitive limits, creating clear boundaries, and enabling parallel work. Tasks properly decomposed achieve 3x higher completion rates and 60% fewer defects.

When to Use This Skill

Use this skill when:

  • A task feels too big to estimate
  • Unsure where to start
  • Blocked by dependencies
  • Task keeps growing (scope creep)
  • Need to break down an epic or feature

Do NOT use this skill when:

  • Task is already small and clear
  • Doing implementation work
  • Architecture decisions needed (use system-design)

Core Principle

The goal isn't more tasks—it's the right tasks. Tasks small enough to understand completely, large enough to deliver value, independent enough to avoid blocking.

Quick Reference: Cognitive Limits

LimitThresholdImplication
Working memory7±2 itemsMax concepts per task
Context switch recovery23 minutesMinimize task switching
Files examined15-20 maxBound task scope
Days before completion drops2-3 daysKeep tasks under this

Task Duration Success Rates

DurationCompletion Rate
< 2 hours95%
2-4 hours90%
4-8 hours (1 day)80%
2-3 days60%
1 week35%
> 2 weeks<10%

Diagnostic States

TD1: Too Big to Understand

Symptoms: Estimates range wildly, can't hold all requirements in mind, more than 7 concepts to track

Interventions:

  • Apply INVEST criteria: Independent, Negotiable, Valuable, Estimable, Small, Testable
  • Use vertical slicing (each slice is independently deployable)
  • Apply walking skeleton (minimal end-to-end first)

TD2: No Clear Entry Point

Symptoms: Multiple valid starting points, paralysis, everything seems connected

Interventions:

  • Front-load risk: start with highest-uncertainty items
  • Tracer bullet: minimal proof of concept
  • Find the walking skeleton: thinnest slice through all layers

TD3: Dependency Problems

Symptoms: "Blocked on X", diamond dependencies, coordination overhead

Interventions:

  • Interface contracts: define API, mock while implementing
  • Feature flags: deploy independently, enable when ready
  • Branch by abstraction: create layer, swap implementations

TD4: No Clear Done Criteria

Symptoms: "Almost done" forever, no way to verify completion

Interventions:

  • Define acceptance criteria (Given/When/Then)
  • Time-box to force prioritization
  • Define explicit out-of-scope items

TD5: Scope Creep

Symptoms: Task keeps growing, "while we're here" additions

Interventions:

  • Freeze scope, spawn new tasks for additions
  • Define minimum viable version
  • Ship smallest version that solves the problem

TD6: Need Spike First

Symptoms: Estimate variance > 4x, new technology, multiple approaches

Interventions:

  • Time-boxed spike (8 hours max)
  • Deliverables: options, POC, trade-offs, revised estimate
  • Spike then implement pattern

Decomposition Patterns

Vertical Slicing (Preferred for Features)

Feature: User Profile Management

Slice 1: View basic profile (4h)
  - UI: Profile display
  - API: GET /profile
  - DB: Read profile

Slice 2: Edit profile name (6h)
  - UI: Edit dialog
  - API: PATCH /profile/name
  - DB: Update profile

Each slice is independently deployable

Walking Skeleton (For New Systems)

Minimal end-to-end first:
1. Hello World page
2. One GET endpoint
3. Single table
4. Basic deploy

Then flesh out incrementally

Tracer Bullet (Validate Architecture)

Step 1: Minimal Service A (1h) - Hardcoded response
Step 2: Minimal Service B (1h) - Simple transformation
Step 3: Integrate (2h) - Prove they communicate

Total: 4 hours to decision point

Estimation Techniques

Complexity Sizing (Fibonacci)

PointsMeaning
1Trivial, < 1 hour
2Simple, 1-2 hours
3Standard, 2-4 hours
5Moderate, 4-8 hours
8Complex, 1-2 days
13Very complex, 2-3 days
21Too large, must decompose

Three-Point Estimation

O = Optimistic (everything perfect)
L = Likely (normal case)
P = Pessimistic (major issues)

PERT estimate: (O + 4L + P) / 6

Anti-Patterns

Big Bang Delivery

Building complete system before any delivery. Fix: Vertical slices, incremental value.

Technical Tasks Without Value

"Set up database," "Create service layer." Fix: Include in feature tasks: "User can view products (includes DB)."

Research Forever

Unbounded investigation. Fix: Time-boxed spikes with deliverables.

Perfect Decomposition

Over-analyzing before starting. Fix: Decompose next 2 weeks. Details for later work emerge.

Decomposition Checklist

Before starting any task:

  • Can hold all requirements in working memory?
  • Duration under 2-3 days?
  • Clear acceptance criteria exist?
  • Dependencies identified and broken where possible?
  • Can be completed independently?
  • Delivers verifiable value?
  • Estimate confidence is high?

If any "no" → further decomposition needed.

Related Skills

  • github-agile - Track decomposed work as issues
  • system-design - Understand architectural boundaries
  • requirements-analysis - Clarify unclear requirements
  • code-review - Review after implementation

平台分布

Claude Code

29.04%
按下载量换算1,012

OpenCode

24.5%
按下载量换算854

Gemini CLI

15.76%
按下载量换算549

Cursor

12.5%
按下载量换算436

Antigravity

7.08%
按下载量换算247

Codex

2.98%
按下载量换算104

安全审计

Gen Agent Trust Hub

通过

Socket

通过

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/jwynia/agent-skills --skill task-decomposition;npx skills add jwynia/agent-skills --skill "task-decomposition" 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。

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