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.