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task-decomposer任务分解器

Agent Skill

task-decomposer 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。

总安装

630

周安装

26

GitHub Stars

218

下载量

206
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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-decomposer(任务分解器)
来源仓库:https://github.com/mathews-tom/praxis-skills
仓库路径:skills/task-decomposer
安装命令:
npx skills add https://github.com/mathews-tom/praxis-skills --skill task-decomposer
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/mathews-tom/praxis-skills --skill task-decomposer

简介

task-decomposer 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词快速定位候选结果时使用。

  • 适用于任务分解和步骤拆分等研究检索场景。
  • 通过 npx skills add 命令从 GitHub 仓库安装,需确认权限范围和文件读写操作。
  • 建议结合原始 README 核验具体用法,注意维护状态和网络访问限制。
  • 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。

SKILL.md

Task Decomposer

Transforms ambiguous feature requests into concrete, implementable task sequences: identifies acceptance criteria, decomposes into phased work items with effort sizing, maps dependencies and parallelization, enumerates edge cases, plans testing, and flags risks — producing a ready-to-execute task board.

When to use this skill vs native decomposition: The base model decomposes features well in an ad-hoc format. Use this skill specifically when you need the structured output: phased task tables with dependency mapping, parallelization flags, risk flags, and integrated test strategy. If you just need a quick list of steps, ask directly without invoking this skill.

Reference Files

FileContentsLoad When
references/decomposition-patterns.mdFeature → task decomposition strategies, granularity guidelinesAlways
references/edge-case-checklist.mdCommon edge case categories by domain (web, API, data, CLI)Edge case identification needed
references/dependency-mapping.mdDependency graph construction, critical path identificationMulti-task breakdown
references/sizing-guide.mdEffort estimation guidance (S/M/L), complexity indicatorsEffort sizing needed

Prerequisites

  • Feature description or requirements (can be vague — the skill handles ambiguity)
  • Project context (tech stack, existing architecture, team size)

Workflow

Phase 1: Understand the Feature

  1. Extract the user-facing goal — What does this feature enable the user to do? If unclear, state assumptions explicitly.
  2. Define acceptance criteria — What must be true for this feature to be "done"? Express as testable statements: "User can X", "System does Y when Z."
  3. Identify non-functional requirements — Performance, security, accessibility, backwards compatibility constraints.
  4. Clarify scope boundaries — What is explicitly out of scope? State this to prevent scope creep during implementation.

Phase 2: Decompose into Tasks

Break the feature into tasks at the right granularity:

GranularitySizeExample
Too coarse"Build the search feature"Not actionable
Right level"Add full-text search index to products table"Single PR, testable
Too fine"Import the search library"Not independently meaningful

Right granularity test: Each task should be completable in a single PR, testable in isolation, and deliverable independently (even if not user-visible alone).

Group tasks into phases:

PhasePurposeContains
FoundationData models, schemas, interfacesTypes, database tables, API contracts
Core logicBusiness logic, algorithmsThe actual feature implementation
IntegrationConnecting components, API endpointsRoutes, controllers, wire-up
PolishEdge cases, error handling, UXValidation, error messages, loading states

Phase 3: Identify Edge Cases

For each task, enumerate edge cases:

  1. Input boundaries — Empty, null, maximum size, special characters
  2. State transitions — Concurrent modification, interrupted operations
  3. Error conditions — Network failures, invalid data, permission denied
  4. Backwards compatibility — Existing data, existing API consumers

Phase 4: Plan Testing

For each task, identify what to test:

Test LevelWhat to TestWho Writes
UnitIndividual functions, pure logicDuring implementation
IntegrationComponent interactions, API endpointsAfter integration phase
ManualUser flows, visual correctnessAfter polish phase

Phase 5: Map Dependencies

Identify which tasks depend on others:

  1. Hard dependencies — Task B requires Task A's output (database table must exist before writing queries)
  2. Soft dependencies — Task B benefits from Task A but could use a stub
  3. No dependency — Tasks can be done in parallel

Phase 6: Flag Risks

For each risk, identify mitigation:

Risk TypeExampleMitigation
Technical unknown"Never used WebSockets before"Spike/prototype first
External dependency"Requires API access we don't have"Request early, use mocks
Scope uncertainty"Requirements may change"Implement core first, defer edge cases
Performance risk"May be slow with 1M rows"Add benchmark task, define acceptable threshold

Output Format

## Task Decomposition: {Feature Name}

### Feature Summary
{One paragraph describing what this feature does and why}

### Acceptance Criteria
- [ ] {Testable statement 1}
- [ ] {Testable statement 2}
- [ ] {Testable statement 3}

### Scope
- **In scope:** {what's included}
- **Out of scope:** {what's excluded}

### Task Breakdown

#### Phase 1: Foundation
| # | Task | Effort | Dependencies | Parallel |
|---|------|--------|--------------|----------|
| 1.1 | {task description} | {S/M/L} | None | Yes |
| 1.2 | {task description} | {S/M/L} | 1.1 | No |

#### Phase 2: Core Logic
| # | Task | Effort | Dependencies | Parallel |
|---|------|--------|--------------|----------|
| 2.1 | {task description} | {S/M/L} | 1.x | Yes |
| 2.2 | {task description} | {S/M/L} | 1.x | Yes |

#### Phase 3: Integration
| # | Task | Effort | Dependencies | Parallel |
|---|------|--------|--------------|----------|
| 3.1 | {task description} | {S/M/L} | 2.x | No |

#### Phase 4: Polish
| # | Task | Effort | Dependencies | Parallel |
|---|------|--------|--------------|----------|
| 4.1 | {task description} | {S/M/L} | 3.x | Yes |

### Edge Cases

| # | Edge Case | Handling | Phase |
|---|-----------|----------|-------|
| 1 | {edge case} | {how to handle} | {which phase} |

### Test Strategy

#### Unit Tests
- {Component}: {what to test}

#### Integration Tests
- {Flow}: {what to test}

#### Manual Verification
- {Scenario}: {what to check}

### Risk Flags
- {Risk}: {mitigation strategy}

Calibration Rules

  1. Right granularity. Each task should be 1-3 days of work. Larger → decompose further. Smaller → merge into a parent task.
  2. Testable acceptance criteria. "Make search work" is not testable. "Search returns relevant results within 200ms for queries up to 100 characters" is testable.
  3. Dependencies are sacred. If Task B truly depends on Task A, mark it. False dependencies slow teams down; missing dependencies cause integration failures.
  4. Edge cases are not optional. Every feature has edge cases. If the edge case list is empty, the analysis is incomplete.
  5. Parallel = velocity. Maximize parallel tasks. If 4 tasks can be done simultaneously, the phase takes the duration of the longest, not the sum.

Error Handling

ProblemResolution
Feature description is vagueState assumptions, decompose what's known, mark uncertain tasks with "pending clarification."
Feature is too large (20+ tasks)Split into multiple features. A feature that takes months is a project, not a feature.
No clear acceptance criteriaHelp the user define them: "What does done look like? What would you demo?"
Technical stack unknownDecompose at the logical level (data model, business logic, API, UI) without implementation specifics.

When NOT to Decompose

Push back if:

  • The task is already atomic (single function, single file change) — just do it
  • The user wants time estimates, not task breakdown — use estimate-calibrator instead
  • The feature is exploratory (research, prototype) — decomposition assumes known scope

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.75%
按下载量换算74

Claude

29.41%
按下载量换算61

Cursor

17.56%
按下载量换算36

Gemini CLI

8.27%
按下载量换算17

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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