task-decomposition
Breaking complex user goals into subtasks that agents can handle.
- Installs
- 160
- Last 24h
- —
- Trending rank
- —
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/owl-listener/ai-design-skills --skill task-decomposition- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads task-decomposition automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Task Decomposition
Users come with goals, not subtasks. Task decomposition is how a multi-agent system breaks a complex user goal into pieces that individual agents can handle — and then reassembles the results into something coherent.
Decomposition Strategies
- Sequential decomposition: Break the goal into ordered steps. Step 1 must complete before Step 2 starts.
- Parallel decomposition: Break the goal into independent parts that can be worked on simultaneously.
- Hierarchical decomposition: Break the goal into sub-goals, then break each sub-goal into tasks.
- Conditional decomposition: The next step depends on the result of the current step. Different results lead to different paths.
- Iterative decomposition: Start with a rough version, then refine through multiple passes.
Designing Decomposition Rules
For each type of user goal the system handles:
- What's the entry point? How does the system receive the goal?
- What are the subtasks? List all possible subtasks for this goal type.
- What are the dependencies? Which subtasks depend on others' outputs?
- What's the critical path? Which sequence of subtasks determines the minimum completion time?
- What can be parallelised? Which subtasks can run simultaneously?
- What's the reassembly logic? How do subtask results combine into the final output?
Granularity
How finely to decompose matters:
- Too coarse: Single agents get tasks that are too complex, leading to lower quality
- Too fine: Overhead from handoffs exceeds the benefit of specialisation
- Just right: Each subtask matches one agent's sweet spot in terms of scope and complexity
Handling Ambiguity
User goals are often ambiguous. The system needs to:
- Clarify before decomposing: Ask the user to specify when the goal is unclear
- Decompose tentatively: Start with a plan and adjust as information emerges
- Recompose when needed: If decomposition was wrong, restructure without starting over
Design Artefacts
- Task decomposition trees for each goal type
- Dependency maps showing subtask relationships
- Parallelisation specifications
- Reassembly logic definitions
- Ambiguity handling protocols
FAQ
What does the task-decomposition skill do?
Breaking complex user goals into subtasks that agents can handle.
How do I install task-decomposition?
Run npx skills add https://github.com/owl-listener/ai-design-skills --skill task-decomposition in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/task-decomposition/ (personal) or .claude/skills/task-decomposition/ (project).
Which AI agents can use task-decomposition?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is task-decomposition safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains task-decomposition?
It is published by owl-listener in owl-listener/ai-design-skills. It has 160 recorded installs.
More from owl-listener/ai-design-skills
system-prompt-structure
owl-listener/ai-design-skills
Open the skill to read its SKILL.md instructions.
guardrail-design
owl-listener/ai-design-skills
Open the skill to read its SKILL.md instructions.
constraint-specification
owl-listener/ai-design-skills
Open the skill to read its SKILL.md instructions.
generative-ui
owl-listener/ai-design-skills
Open the skill to read its SKILL.md instructions.
conversation-patterns
owl-listener/ai-design-skills
Open the skill to read its SKILL.md instructions.
progressive-disclosure
owl-listener/ai-design-skills
Open the skill to read its SKILL.md instructions.
Popular productivity & automation skills
agent-browser
vercel-labs/agent-browser
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools.
lark-doc
open.feishu.cn
飞书云文档（Docx / Wiki）内容操作：读取、创建、编辑文档，插入或下载图片附件，以及操作思维笔记。用户提供文档 URL/token（包括 doubao.com 的 /docx/、/wiki/）时使用；按 URL 路径/token 而非域名路由；/page/ 是妙搭应用，非飞书云文档。文档内嵌资源按读取参考中的统一规则分流。独立评论操作走 lark-drive；随正文读取评论使用 docs +fetch。表格或 Base 内部数据操作不在本 skill。
lark-base
open.feishu.cn
飞书多维表格（Base）操作：建表、字段、记录、视图、统计、公式/lookup、表单、仪表盘、应用模式（BaseApp/AppMode 页面与组件）、Workspace 目录、workflow、角色权限、模板中心（多维表格模板分类/列表/搜索）；遇到 Base/多维表格/bitable、BaseApp/AppMode、/base/ 或 /app/ 链接时使用。BaseApp 不走 lark-apps；文件导入/导出转 lark-drive，认证/授权转 lark-shared。
lark-drive
open.feishu.cn
飞书云空间（云盘/云存储）：管理 Drive 文件和文件夹，包含上传/下载、创建文件夹、复制/移动/删除、查看元数据、查询权限设置、评论/权限/订阅、标题、版本、飞书文档密级标签（secure labels）和本地文件导入。用户需要整理云盘目录、处理云空间资源 URL/token、判断链接类型/真实 token/标题，或导入 Word/Markdown/Excel/CSV/PPTX/.base 为 docx/sheet/bitable/slides 时使用；doubao.com 云空间 URL/token 也按资源路径和 token 路由，不回退 WebFetch。不负责：文档内容编辑（走 lark-doc）、表格/Base 表内数据操作（走 lark-sheets/lark-base）、知识空间节点/成员管理（走 lark-wiki）、原生 Markdown 文件读写/patch/diff（走 lark-markdown）。
lark-shared
open.feishu.cn
Use for lark-cli setup/auth tasks: auth login/status/logout, user vs bot identity, business-domain permissions (--domain, including all/docs/drive), missing scopes, revoking authorization, or handling notice JSON.
lark-im
open.feishu.cn
飞书即时通讯：收发消息和管理群聊。发送和回复消息、搜索聊天记录、管理群聊成员、上传下载图片和文件、管理表情回复、发送应用内/短信/电话加急、发送和处理交互卡片（Interactive Card）、监听卡片按钮回调（card.action.trigger）。当用户需要发消息、查看或搜索聊天记录、下载聊天中的文件、查看群成员、搜索群、创建群聊或话题群、管理标记数据、管理 Feed 置顶（添加/移除/查询置顶会话）、管理标签数据、处理卡片回调时使用。