generating-prd-json-from-prd-md

generating-prd-json-from-prd-md is a skill for Claude Code, Codex from qte77/claude-code-plugins. It costs 46 tokens per session (651 once invoked), scanned A, original, Apache-2.0.

Generates prd.json task tracking file from PRD.md requirements document. Use when initializing Ralph loop or when the user asks to convert PRD to JSON format for autonomous execution.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/qte77/claude-code-plugins/generating-prd-json-from-prd-md
Any agent
npx skills add qte77/claude-code-plugins --skill generating-prd-json-from-prd-md
Clone the repo
git clone --depth 1 https://github.com/qte77/claude-code-plugins

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for generating-prd-json-from-prd-md

README.md
[![agentmods](https://agentmods.dev/badge/skills/qte77/claude-code-plugins/generating-prd-json-from-prd-md.svg)](https://agentmods.dev/skills/qte77/claude-code-plugins/generating-prd-json-from-prd-md)
Your own site
<a href="https://agentmods.dev/skills/qte77/claude-code-plugins/generating-prd-json-from-prd-md"><img src="https://agentmods.dev/badge/skills/qte77/claude-code-plugins/generating-prd-json-from-prd-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 651 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00046 $0.00651
Opus 5 $0.00023 $0.00326
Sonnet 5 $0.00009 $0.00130
Haiku 4.5 $0.00005 $0.00065

Measured today against content hash 4082e5fd8c29, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

generating-prd-json-from-prd-md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/ralph/skills/generating-prd-json-from-prd-md/SKILL.md · 92 lines

How it starts

The opening of the file, as written. The whole thing — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PRD to JSON Conversion

Hybrid approach: Python script parses, AI validates and corrects.

Workflow

  1. Dry-run parser (Bash tool) — catch parser issues before writing
python ralph/scripts/generate_prd_json.py --dry-run

Check output for: declared vs parsed story count mismatch, missing stories, empty acceptance/files. If issues found, fix PRD markdown or note for manual correction in step 3.

  1. Run parser (Bash tool)
python ralph/scripts/generate_prd_json.py

Script handles: PRD.md parsing, (depends: ...) extraction, content hashing, state preservation.

  1. Validate (Read tool)

    • Read ralph/docs/prd.json (script output)
    • Read docs/PRD.md (cross-reference)
    • Check against Validation Checklist
  2. Correct errors (Write tool, if needed)

    • Fix issues found
    • Recompute content_hash if title/description/acceptance changed
    • Write corrected ralph/docs/prd.json
  3. Report

    • Story count and status
    • Corrections made
    • Suggest: make ralph_run

Validation Checklist

For each story, verify:

  • id follows STORY-XXX format
  • title is 3-7 words, matches PRD.md feature
  • description is non-empty
  • acceptance array is non-empty
  • files array contains valid paths (if specified in PRD.md)
  • content_hash is 64-char hex string
  • depends_on references valid STORY-XXX IDs (no circular deps, no self-refs)

Cross-reference with PRD.md:

  • All #### Feature N: headings have corresponding stories
  • Story order matches PRD.md feature order
  • (depends: STORY-XXX) syntax correctly parsed

Common Issues to Correct

Issue Correction
Empty acceptance Extract from description or PRD.md feature
Invalid depends_on reference Remove non-existent story IDs
Circular dependency Remove one direction
Missing content_hash Recompute from title+description+acceptance
Duplicate story IDs Renumber sequentially

Read the full file on GitHub · 92 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. today First seen · 92 lines · 46 tokens per session scan A 4082e5fd8c29

Subscribe to this mod's changes

generating-prd-json-from-prd-md is a skill published in the GitHub repository qte77/claude-code-plugins (2 stars, last pushed 5d ago), licensed Apache-2.0. It adds 46 tokens to every session and 651 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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