mad-decompose

Decompose feature design documents into dependency-ordered milestones with generated idea.md files.

Updated May 7, 2026
One-click install
npx skills add https://github.com/tmalcolm-0607/mad-council-claw --skill mad-decompose
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: mad-decompose
Source: https://github.com/tmalcolm-0607/mad-council-claw/tree/main/.claude/skills/mad-decompose
Command: npx skills add https://github.com/tmalcolm-0607/mad-council-claw --skill mad-decompose

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Large feature design documents are difficult to manually break into manageable, dependency-ordered milestones without missing implementation gaps, creating unreviewable large PRs, or introducing integration risks between horizontal work layers. This Skill eliminates that manual overhead by automating the full decomposition workflow with built-in validation guardrails.

Core Features & Use Cases

  • Parallel Gap Analysis: Spawns 3 specialized agent analysts to map existing code, backlog items, and design document features to identify unplanned work.
  • Validated Milestone Grouping: Synthesizes analysis into dependency-ordered, vertical-slice milestones with automatic size calibration, DAG validation, and integration point documentation.
  • Batched Idea Generation: Produces scoped idea.md files for each milestone that align with MAD kit standards, ready to feed into the /mad-spec workflow.
  • Use Case: If you have a 2000-line feature design covering 20 API endpoints and 12 data entities, this Skill will automatically split it into 6-8 shippable milestones, each with a fully scoped idea file and a reviewable milestone map.

Quick Start

Use the mad-decompose skill to decompose your feature design document at docs/design/feature-overview.md into dependency-ordered, shippable milestones with generated idea files.

Frequently Asked Questions about mad-decompose

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I break a large feature design document into shippable milestones?

To break a feature design document into shippable milestones, you can use automated decomposition to split large specs into dependency-ordered vertical slices. This eliminates manual gap analysis and prevents unreviewable large PRs by mapping integration points across entities and endpoints.

What is parallel gap analysis in software milestone planning?

Parallel gap analysis in milestone planning uses specialized agent analysts to simultaneously map existing code, backlog items, and design features. This process identifies unplanned work and missing dependencies before grouping features into validated, shippable vertical slices.

How do I generate scoped idea files for vertical slice milestones?

Generating scoped idea files for vertical slice milestones involves batched creation of idea.md documents aligned with governance standards. These files are automatically scoped for each decomposed milestone, ready to feed directly into downstream specification workflows.

Can I decompose a design doc covering multiple endpoints and data entities automatically?

Yes, you can automatically decompose design documents covering multiple endpoints and data entities. The process handles complex specs by calibrating milestone sizes, validating dependency DAGs, and documenting integration points for iterative development.

What is the best way to avoid unreviewable large PRs in feature development?

The best way to avoid unreviewable large PRs in feature development is to decompose design documents into dependency-ordered, vertical-slice milestones. This approach automatically splits large features into 6-8 shippable milestones with scoped idea files for iterative development.

When should I not use automated design doc decomposition?

You should not use automated design doc decomposition for small features that do not cover multiple entities, endpoints, or infrastructure components. It is designed for large specifications requiring vertical slice splitting, DAG validation, and parallel code and backlog analysis.