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task-decomp任务分解

Agent Skill

task-decomp 用于查找、检索和筛选相关信息,适合在 OpenClaw 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

16,848

周安装

675

GitHub Stars

1

下载量

5,454
OpenClaw

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

MIT-0

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-decomp(任务分解)
来源仓库:https://github.com/nathancjackson/task-decomp
安装命令:
openclaw skills install task-decomp
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install task-decomp

简介

复杂多步骤任务分解与跟踪管理工具。task-decomp 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

  • 支持并行执行、进度监控与依赖感知子任务拆分。
  • 适用于长期项目规划与学习优化场景。
  • 安装前需确认权限范围、维护状态及是否持久化任务状态。
  • 建议结合原始 README 核验依赖解析与失败重试策略。

SKILL.md

name
task-decomp
description
Plan, track, and learn from complex multi-step tasks. Decomposes requests into dependency-aware subtasks with parallel execution, progress tracking, and a learning loop that improves future plans from past outcomes. Use when: (1) A request involves 3+ steps with dependencies, (2) Work spans multiple tools or sub-agents, (3) User says 'plan this out', 'break this down', or 'how should we approach this', (4) Managing a project, workflow, or multi-phase build, (5) Coordinating parallel workstreams. Improves over time — completed plans feed back into planning intelligence. NOT for: simple one-shot requests, single tool calls, or conversational exchanges.

Task Decomposition

Plan complex work. Track it. Learn from it. Get better at planning over time.

Plan Format

Store plans in plans/ (workspace-relative). Name: [slug].plan.md. Multiple concurrent plans supported.

# Plan: Deploy new API
Started: 2026-03-03 11:00
Status: in-progress
Revised: 1

## Tasks

- [x] 1. (S) Provision database — Postgres 16, endpoint saved to .env
- [ ] 2. (M) Build auth middleware (depends: 1)
- [ ] 3. (M) Build CRUD endpoints (depends: 1)
      ↳ parallel with 2
- [ ] 4. (L) Integration tests (depends: 2, 3)
- [ ] 5. (S) Deploy to staging (depends: 4) ⚠️ blocked: waiting on VPN access
      spawned: session-k9x2

## Retro
<!-- filled on completion -->

Notation

  • Size: (S) <30min, (M) 30min-2h, (L) 2h+
  • Dependencies: (depends: 1, 3) = must complete first
  • Parallel: ↳ parallel with N = concurrent with task N
  • Blocked: ⚠️ blocked: [reason]
  • Delegated: spawned: [session-id]
  • Done: - [x] with outcome after dash: — result summary

Planning

  1. Read the FULL request before decomposing
  2. Identify boundaries: different tools, contexts, or outputs = different tasks
  3. Mark real dependencies only — parallel what CAN be parallel
  4. Size each task (S/M/L) — makes progress reports honest
  5. Action-oriented names: "Install X", "Configure Y", "Verify Z"
  6. Check plans/ for similar past plans — reuse what worked, avoid what didn't

Execution

  1. Work in dependency order, parallelize where noted
  2. Update plan after each TASK completes (not each tool call)
  3. Blocked? Mark it, work next unblocked task
  4. Record outcomes — future you needs them

Revision

Plans change mid-flight. When they do:

  • Insert: Add with next number, update downstream depends:
  • Remove: ~~Strikethrough~~, don't renumber (preserves refs)
  • Reorder: Update depends: only
  • Bump the Revised: counter

Don't follow a bad plan to completion.

Resume (After Restart)

When you find an existing plan:

  1. Read it — check Status
  2. Find first unchecked, unblocked task
  3. Quick sanity check that prior tasks still hold
  4. Continue — or revise first if context changed

Failure

  • Task fails → note it, assess: can downstream tasks still run?
  • Unrecoverable → Status: abandoned, explain why
  • Always record what DID work — partial progress has value

Sub-agent Delegation

  • One sub-agent per independent BRANCH, not per task
  • Record session ID on the task line
  • Don't poll in loops — check on events or when asked

Progress Report

When asked "status?" or "where are we?":

📋 Plan: Deploy new API
Progress: 3/7 tasks (1L + 2S remaining)
Current: Task 4 (L) — running integration tests
Blocked: Task 5 — waiting on VPN access
Revised: 1x

Size-aware > task-count. "1/5 done" is misleading when the 4 remaining are all (L).

Learning Loop ← what makes plans improve

Retro (on completion)

When a plan finishes (completed or abandoned), fill the ## Retro section:

## Retro
- **What worked:** Parallelizing tasks 2+3 saved ~1h
- **What didn't:** Underestimated task 4 (sized M, was actually L)
- **Sizing accuracy:** 3/5 tasks sized correctly
- **Dependencies missed:** Task 5 actually needed task 2 directly, not just via 4
- **Reusable pattern:** [If this plan type recurs, note the template]

Patterns File

Maintain plans/patterns.md — distilled lessons from retros:

# Planning Patterns (learned from retros)

## Sizing
- API integration tasks: usually (M), not (S)
- "Write tests" is always bigger than you think → size up one level
- Database migrations with data backfill: always (L)

## Dependencies
- Auth must come before any authenticated endpoint work
- Don't parallelize tasks that write to the same config file

## Templates
- **API build:** provision → auth + endpoints (parallel) → tests → deploy
- **Research report:** gather sources → analyze (parallel per source) → synthesize → review

This file gets checked during Step 6 of Planning ("check past plans"). Over time, sizing gets more accurate, dependency mistakes stop repeating, and common project types get reusable templates.

Decay

Review patterns.md monthly. Remove patterns that:

  • Haven't applied in 30+ days
  • Were wrong more than once
  • Are too project-specific to generalize

Archive

Completed/abandoned plans → rename [date]-[slug].plan.md:

plans/
├── deploy-api.plan.md              # active
├── patterns.md                     # learned patterns
├── 2026-03-01-setup-acw.plan.md    # archived
└── 2026-03-02-osint-recon.plan.md  # archived

Anti-patterns

  • Over-decomposition: 15 tasks for 4 steps of real work
  • Phantom dependencies: Marking sequential what's actually parallel
  • Plan worship: Following a wrong plan because it exists
  • Size blindness: "4/5 done!" when the remaining task is (L)
  • Skipping retros: No retro = no learning = same mistakes forever

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

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

补充不同宿主或平台的使用分布数据

能力 5

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

OpenClaw

90.29%
按下载量换算4,924

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

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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。

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