firefrost-gaming/claude-skills-reference

Files

Reza Rezvani 4b7a084ee3 feat(code-to-prd): expand to fullstack — add NestJS, Django, Express, FastAPI support

- Rename frontend_analyzer.py → codebase_analyzer.py — now detects backend
  frameworks via package.json (NestJS, Express, Fastify) and project files
  (manage.py, requirements.txt for Django, FastAPI, Flask)
- Add backend route extraction: NestJS @Controller/@Get decorators,
  Django urls.py path() patterns
- Add model/entity extraction: Django models.Model fields, NestJS @Entity
  and DTO classes
- Add stack_type detection (frontend / backend / fullstack) to analysis output
- SKILL.md: add Supported Stacks table, backend directory guide, backend
  endpoint inventory template, backend page type strategies, backend pitfalls
- references/framework-patterns.md: add NestJS, Express, Django, DRF, FastAPI
  pattern tables + database model patterns + backend validation patterns
- references/prd-quality-checklist.md: add backend-specific checks (endpoints,
  DTOs, models, admin, middleware, migrations)
- Update all descriptions and keywords across plugin.json, settings.json,
  marketplace.json, and /code-to-prd command

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2026-03-17 12:28:30 +01:00

2.5 KiB

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

/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

Scan — Run codebase_analyzer.py to detect framework, routes, APIs, enums, and project structure
Scaffold — Run prd_scaffolder.py to create prd/ directory with README.md, per-page stubs, and appendix files
Analyze — Walk through each page following the Phase 2 workflow: fields, interactions, API dependencies, page relationships
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/SKILL.md
product-team/code-to-prd/scripts/codebase_analyzer.py
product-team/code-to-prd/scripts/prd_scaffolder.py
product-team/code-to-prd/references/prd-quality-checklist.md

2.5 KiB Raw Blame History