task-decomposition
Task Decomposition breaks down epics into 4-5 parallel work streams, creating concrete tasks with Given/When/Then acceptance criteria, effort estimates (S/M/L/XL), and dependency graphs. Use this skill when you need to translate a high-level epic into executable, parallelizable work items that maintain traceability to product requirements and coordinate across multiple development streams.
git clone --depth 1 https://github.com/a5c-ai/babysitter /tmp/task-decomposition && cp -r /tmp/task-decomposition/library/methodologies/ccpm/skills/task-decomposition ~/.claude/skills/task-decompositionSKILL.md
# Task Decomposition Break epics into parallelizable tasks with acceptance criteria, effort estimates, and dependency graphs. ## Agent Task Analyst - `task-analyst` ## Workflow 1. Analyze epic and identify 4-5 parallel work streams 2. Decompose each stream into concrete tasks (parallel) 3. Set acceptance criteria in Given/When/Then format 4. Estimate effort (S/M/L/XL) and set parallelization flags 5. Build cross-stream dependency graph 6. Validate coverage against PRD user stories 7. Fill gaps with additional tasks if needed 8. Write task files to .claude/epics/<featureName>/<N>.md ## Inputs - `projectName` - Project name - `featureName` - Feature identifier - `epic` - Epic from Phase 2 - `prd` - PRD from Phase 1 - `parallelAgents` - Max parallel agents (default: 5) ## Outputs - Task list with acceptance criteria and effort estimates - Work stream definitions - Dependency graph with execution waves - Coverage report with PRD traceability ## Process Files - `ccpm-task-decomposition.js` - Standalone decomposition - `ccpm-orchestrator.js` - Phase 3 of full lifecycle
Coordinate Crew (persistent) and Polecat (transient) agents using Gas Town's hook-based work distribution and GUPP principle.
System and API design guidance covering component boundaries, data flow, integration patterns, and scalability considerations.
This skill should be used when the user asks to "find skills in the wild", "assimilate popular workflows", "discover SKILL.md files in repos", "research external skills", "find workflow patterns", "survey the skill landscape", "what skills exist out there", or wants to investigate public repositories for extractable processes, babysitter plugins, and reusable procedural insights. Searches GitHub for SKILL.md files, classifies repos by archetype, and maintains structured research under docs/reference-repos/.
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This skill should be used when the user asks to "babysit issues", "work on assigned issues", "check a5c-agent issues", "process babysitter issues", or wants to find and work on open GitHub issues assigned to a5c-agent in the babysitter repo.