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d-o-hub

task-decomposition

by d-o-hub

A modular Rust-based self-learning episodic memory system for AI agents, featuring hybrid storage with Turso (SQL) and redb (KV), async execution tracking, reward scoring, reflection, and pattern-based skill evolution. Designed for real-world applicability, maintainability, and scalable agent workflows.

3🍴 0📅 Jan 23, 2026

SKILL.md


name: task-decomposition description: Break down complex tasks into atomic, actionable goals with clear dependencies and success criteria. Use when planning multi-step projects, coordinating agents, or decomposing complex requests.

Task Decomposition

Break down complex tasks into atomic, actionable goals with clear dependencies.

When to Use

  • Complex user requests with multiple components
  • Multi-phase projects requiring coordination
  • Tasks that could benefit from parallel execution
  • Planning agent coordination strategies

Decomposition Framework

1. Requirements Analysis

  • Primary objective
  • Implicit requirements (quality, performance)
  • Constraints (time, resources)
  • Success criteria

2. Goal Hierarchy

Main Goal
├─ Sub-goal 1
│  ├─ Task 1.1 (atomic)
│  └─ Task 1.2 (atomic)
├─ Sub-goal 2
└─ Sub-goal 3

3. Dependency Types

TypeSymbolExample
SequentialA → B → CB needs A's output
ParallelA─┐ B─┐ C─┘Independent, concurrent
ConvergingA─┐ B─┼─> DD needs A, B, C
ResourceA, BSequential or pooled

4. Success Criteria

For each task:

  • Input: What data/state is needed
  • Output: What artifacts will be produced
  • Quality: Performance, testing, docs requirements

Decomposition Patterns

PatternUse Case
Layer-BasedArchitectural changes (data, logic, API, test, docs)
Feature-BasedNew features (MVP, error handling, optimization, integration)
Phase-BasedLarge projects (research, foundation, core, integration, polish)
Problem-SolutionDebugging (reproduce, diagnose, design, fix, verify, prevent)

Quality Checklist

✓ Atomic and actionable ✓ Dependencies clearly identified ✓ Success criteria measurable ✓ No task too large (>4 hours) ✓ Parallelization opportunities identified

✗ Tasks too large or vague ✗ Missing dependencies ✗ Unclear success criteria ✗ Missing quality/testing tasks

Integration with GOAP

Task decomposition is Phase 1 of GOAP:

  1. Receive request
  2. Apply decomposition
  3. Create execution plan
  4. Execute with monitoring
  5. Report results

Score

Total Score

75/100

Based on repository quality metrics

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