task-decomposition
Breaking complex user goals into subtasks that agents can handle.
适合你，如果需要将用户模糊需求转化为结构化步骤
/ 通过 npx 安装 校验哈希
npx oh-my-skill add owl-listener/ai-design-skills/task-decomposition/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- owl-listener/ai-design-skills/task-decomposition/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify owl-listener/ai-design-skills/task-decomposition安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
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怎么用
商店整理自技能原文 · 版本 f41b650 · 表述以原文为准它做什么
装上后，Claude 会将用户的复杂目标拆解成多个子任务，按顺序、并行或层次等策略执行，并最终合并结果。
什么时候触发
当用户提出一个模糊或复杂的、无法由单个代理直接完成的目标时触发。
装好后可以这样说
Claude 会分解为多个子任务并逐步处理。
Claude 会按顺序或并行执行这些子任务。
技能原文 SKILL.md
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
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