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task-decomposition

task-decomposition

github.com/owl-listenerAgent workflows195167 installsUpdated 21w ago
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About task-decomposition

A design skill for breaking complex goals into agent-sized tasks and combining their results. It covers dependency, parallelism, granularity, ambiguity, and reassembly rules for multi-agent systems.

Key features

  1. 01Sequential, parallel, and hierarchical strategies
  2. 02Conditional and iterative decomposition
  3. 03Map dependencies and critical paths
  4. 04Set task granularity and reassembly logic
  5. 05Handle ambiguity and revise task plans

Use cases

  1. 01Plan subtasks for a complex user goal
  2. 02Identify tasks that can run concurrently
  3. 03Restructure a plan when results change
  4. 04Define how agents' outputs form a final result

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/owl-listener/ai-design-skills --skill task-decomposition

After installing, type/task-decompositionin Claude Code to confirm it loaded.

Details

From the project README

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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