plan-polish

Convert rough plans and intake data into a track-aware Technical Design Document.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/quantfiction/dotfiles --skill plan-polish
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: plan-polish
Source: https://github.com/quantfiction/dotfiles/tree/main/claude/plugins/global-skills/skills/plan-polish
Command: npx skills add https://github.com/quantfiction/dotfiles --skill plan-polish

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Converts rough plans and intake data into a detailed, implementation-grade Technical Design Document that autonomous agents can execute with minimal ambiguity.

Core Features & Use Cases

  • Transform Stage 1 inputs (INTAKE.md, ROUGH PLAN) into a detailed, implementable design.
  • Determine track from INTAKE.md and generate a TECHNICAL_DESIGN.md under docs/plans/<project-slug>/ with a track-aware schema (Lite for Track M, Full for Track L).
  • Provide thorough verification notes, architecture sections, and edge-case handling to guide autonomous coding agents.

Quick Start

Provide the intake and rough plan to the AI to generate a complete TECHNICAL_DESIGN.md for your project.

Frequently Asked Questions about plan-polish

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

FAQPage Schema
How do I convert a rough plan into a technical design document for autonomous agents?▼

To convert a rough plan into a technical design document, you provide intake data and research dossiers to generate an implementation-grade design file with architecture outlines, data structures, and validation requirements tailored for autonomous agent execution.

What inputs are required to generate an implementation-grade technical design document?▼

Generating an implementation-grade technical design document requires an INTAKE.md file, a rough plan, and a RESEARCH_DOSSIER.md to apply a track-aware schema that drives the detailed architecture and component outlines.

How does a track-aware schema work when creating technical design documentation?▼

A track-aware schema determines the depth of your technical design documentation by generating either a Lite schema for Track M or a Full schema for Track L, ensuring the output matches the project's specific implementation requirements.

Can I use rough intake data to produce architecture and component outlines for coding agents?▼

Yes, you can use rough intake data to produce architecture and component outlines by processing it into a TECHNICAL_DESIGN.md file that includes thorough verification notes and edge-case handling specifically structured for autonomous coding agents.

What is the best way to structure technical design documents for autonomous agent execution?▼

The best way to structure technical design documents for autonomous agent execution is to use a track-aware schema that provides detailed data structures, architecture sections, and validation requirements, minimizing execution ambiguity.

When do I need a full versus lite track schema for my technical design document?▼

You need a Full track schema for Track L projects and a Lite track schema for Track M projects, with the specific track determined directly from the INTAKE.md data to match the required implementation depth.