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Code to prd

Skill srg-sphynx/MDForge/Sources/MDForge/Resources/SkillLibrary/Product/code-to-prd

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Install
npx -y skills add srg-sphynx/MDForge --skill code-to-prd

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

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Reverse-engineer a frontend codebase into a PRD. Usage: /code-to-prd [path]

SKILL.md

2.6 KB, as published. Nobody here has run it

/code-to-prd

Reverse-engineer a frontend codebase into a complete Product Requirements Document.

Usage

/code-to-prd                    # Analyze current project
/code-to-prd ./src              # Analyze specific directory
/code-to-prd /path/to/project   # Analyze external project

What It Does

  1. Scan — Run codebase_analyzer.py to detect framework, routes, APIs, enums, and project structure
  2. Scaffold — Run prd_scaffolder.py to create prd/ directory with README.md, per-page stubs, and appendix files
  3. Analyze — Walk through each page following the Phase 2 workflow: fields, interactions, API dependencies, page relationships
  4. Generate — Produce the final PRD with all pages, enum dictionary, API inventory, and page relationship map

Steps

Step 1: Analyze

Determine the project path (default: current directory). Run the frontend analyzer:

python3 {skill_path}/scripts/codebase_analyzer.py {project_path} -o .code-to-prd-analysis.json

Display a summary of findings: framework, page count, API count, enum count.

Step 2: Scaffold

Generate the PRD directory skeleton:

python3 {skill_path}/scripts/prd_scaffolder.py .code-to-prd-analysis.json -o prd/

Step 3: Fill

For each page in the inventory, follow the SKILL.md Phase 2 workflow:

  • Read the page's component files
  • Document fields, interactions, API dependencies, page relationships
  • Fill in the corresponding prd/pages/ stub

Work in batches of 3-5 pages for large projects (>15 pages). Ask the user to confirm after each batch.

Step 4: Finalize

Complete the appendix files:

  • prd/appendix/enum-dictionary.md — all enums and status codes found
  • prd/appendix/api-inventory.md — consolidated API reference
  • prd/appendix/page-relationships.md — navigation and data coupling map

Clean up the temporary analysis file:

rm .code-to-prd-analysis.json

Output

A prd/ directory containing:

  • README.md — system overview, module map, page inventory
  • pages/*.md — one file per page with fields, interactions, APIs
  • appendix/*.md — enum dictionary, API inventory, page relationships

Skill Reference

  • product-team/code-to-prd/skills/code-to-prd/SKILL.md
  • product-team/code-to-prd/skills/code-to-prd/scripts/codebase_analyzer.py
  • product-team/code-to-prd/skills/code-to-prd/scripts/prd_scaffolder.py
  • product-team/code-to-prd/skills/code-to-prd/references/prd-quality-checklist.md

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.