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AF code-to-prd

Reverse-engineer any codebase into a complete Product Requirements Document (PRD). Analyzes routes, components, state management, API integrations, and user interactions to produce business-readable documentation detailed enough for engineers or AI agents to fully reconstruct every page and endpoint. Works with frontend frameworks (React, Vue, Angular, Svelte, Next.js, Nuxt), backend frameworks (NestJS, Django, Express, FastAPI), and fullstack applications. Trigger when users mention: generate PRD, reverse-engineer requirements, code to documentation, extract product specs from code, document page logic, analyze page fields and interactions, create a functional inventory, write requirements from an existing codebase, document API endpoints, or analyze backend routes.

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 12 files body ≈ 4 639 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Reverse-engineer any codebase into a complete Product Requirements Document (PRD).

As a process F 48/100 · Will not run — References files that are not bundled: pages/01-user-mgmt-list.md

IntegrationGitHubSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
F
48/100
Will not run
References files that are not bundled: pages/01-user-mgmt-list.md
Tools and files w 18
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 12. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: pages/01-user-mgmt-list.md
  • note frontmatter-key unknown frontmatter key "Name"
  • note frontmatter-key unknown frontmatter key "Tier"
  • note frontmatter-key unknown frontmatter key "Category"
  • note frontmatter-key unknown frontmatter key "Dependencies"
  • note frontmatter-key unknown frontmatter key "Author"
  • note frontmatter-key unknown frontmatter key "Version"

Process rating: all ten parameters 48/100

Will not run. References files that are not bundled: pages/01-user-mgmt-list.md
  • 0Tools and files. 1 referenced file(s) missing: pages/01-user-mgmt-list.md
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 7 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Result and completion. Output format stated, no completion criterion
  • 70When it triggers. States when to use, but not when not to
  • 70Execution cost. Instruction body is 4639 tokens
  • 85Steps. 57 steps, 1 vague phrases
  • 100Consistency. Name and required fields are in place
  • low 13 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +2Single-language instructions
  • +3Description length 778: enough signal without eating the budget
  • +4Structure: 38 headings
  • +3Step-by-step instructions: 57 items
  • +3Output format is stated explicitly
  • +4Has examples (10 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +3All 2 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.