From mece-decomposer
Break down a goal, process, or workflow into MECE components with Agent SDK mapping. Use when user says "decompose", "break down this process", "MECE analysis", "create a decomposition tree", or pastes a JSON/YAML/CSV workflow export to analyze.
How this skill is triggered — by the user, by Claude, or both
Slash command
/mece-decomposer:decomposeThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Decompose a process, goal, or workflow into MECE (Mutually Exclusive, Collectively Exhaustive) components with dual output -- a human-readable tree and structured JSON mapping to Claude Agent SDK primitives.
Decompose a process, goal, or workflow into MECE (Mutually Exclusive, Collectively Exhaustive) components with dual output -- a human-readable tree and structured JSON mapping to Claude Agent SDK primitives.
/decompose <description of what to decompose>
Examples:
/decompose our customer onboarding process from sign-up to first value delivery/decompose the CI/CD pipeline for our microservices architecture/decompose quarterly financial close process/decompose then paste a JSON/YAML/CSV export from a workflow toolIf the user provides structured data (JSON, XML, YAML, CSV, or any workflow/process export), do NOT assume you understand the schema. Ask what the data represents, what key fields mean, and how entities relate. Present your interpretation back, let them correct it, repeat until agreed. For free-text, skip this.
Establish boundary, trigger, and completion criteria. If ambiguous, ask clarifying questions. Do not guess at scope boundaries.
Score candidate dimensions (temporal, functional, stakeholder, state, input-output) using the 4-criteria rubric from the mece-decomposer skill. Document the winner and rationale.
Produce 3-7 L1 components. Apply full MECE validation (see references/validation_heuristics.md).
Decompose each L1. Choose dimension per branch (may differ from L1). Decrease validation rigor with depth per the depth-adaptive schedule.
At each leaf, apply the co-occurrence heuristic. Classify atoms by execution type: agent, human, tool, or external.
Identify data, sequencing, resource, and approval dependencies between branches.
Map atoms to Agent SDK primitives per references/agent_sdk_mapping.md. Assign model tiers.
Run final structural checks. Compute ME/CE scores.
Process Name (orchestration type)
+-- Phase 1 (parallel)
| +-- [agent] Step A (~5m, sonnet)
| +-- [human] Step B (~2h, webhook)
+-- Phase 2 (sequential)
+-- [tool] Step C (~10s, tool_name)
+-- [agent] Step D (~1m, haiku)
Each line: label, execution type in brackets, estimated duration, model tier or integration method.
Full JSON conforming to references/output_schema.md. To validate structurally:
uv run mece-decomposer/skills/mece-decomposer/scripts/validate_mece.py <output.json>
After producing the JSON, call the mece-decompose MCP tool with the full JSON string to render the interactive tree in Claude Desktop, Cowork, or Claude.ai.
After decomposition:
/validate/interview/exportnpx claudepluginhub fblissjr/fb-claude-skills --plugin mece-decomposerGuides creation, editing, and verification of skills for AI coding agents using test-driven development with subagent scenarios. Use when authoring or debugging skills.