Borrowing it
Nothing to install: this file belongs to YougLin-dev/Aha-Loop. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/YougLin-dev/Aha-Loop/main/.agents/skills/prd-converter/SKILL.mdgit clone --depth 1 https://github.com/YougLin-dev/Aha-LoopWrote 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.
[](https://agentmods.dev/skills/youglin-dev/aha-loop/prd-converter)<a href="https://agentmods.dev/skills/youglin-dev/aha-loop/prd-converter"><img src="https://agentmods.dev/badge/skills/youglin-dev/aha-loop/prd-converter/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/youglin-dev/aha-loop/prd-converter"><img src="https://agentmods.dev/badge/skills/youglin-dev/aha-loop/prd-converter.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00047 | $0.02498 |
| Opus 5.5 | $0.00019 | $0.00999 |
| Sonnet 5.5 | $0.00009 | $0.00500 |
| Haiku 4.5 | $0.00005 | $0.00250 |
Grade A, and why
prd-converter 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 2mo ago.
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.
How it starts
The opening of the file, as written. The whole thing — 334 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Aha Loop PRD Converter
Converts existing PRDs to the prd.json format that Aha Loop uses for autonomous execution.
The Job
Take a PRD (markdown file or text) and convert it to prd.json in the scripts/aha-loop directory.
Output Format (v2)
{
"version": 2,
"prdId": "[PRD-XXX from roadmap or PRD filename]",
"project": "[Project Name]",
"branchName": "aha-loop/[feature-name-kebab-case]",
"description": "[Feature description from PRD title/intro]",
"changeLog": [],
"userStories": [
{
"id": "US-001",
"title": "[Story title]",
"description": "As a [user], I want [feature] so that [benefit]",
"acceptanceCriteria": [
"Criterion 1",
"Criterion 2",
"Typecheck passes"
],
"priority": 1,
"passes": false,
"researchTopics": [
"Question about technology or best practice",
"Question about existing patterns"
],
"researchCompleted": false,
"learnings": "",
"implementationNotes": "",
"notes": ""
}
]
}
New v2 Fields Explained
| Field | Purpose |
|---|---|
version |
Schema version (always 2) |
prdId |
PRD identifier (e.g., PRD-001) for commit message prefixes |
changeLog |
Array of plan modifications made during execution |
researchTopics |
Questions to investigate before implementing the story |
researchCompleted |
Whether research phase is done for this story |
learnings |
Knowledge gained during implementation (filled by Aha Loop) |
implementationNotes |
Guidance from research phase for implementation |
Story Size: The Number One Rule
Each story must be completable in ONE Aha Loop iteration (one context window).
Aha Loop spawns a fresh AI instance per iteration with no memory of previous work. If a story is too big, the LLM runs out of context before finishing and produces broken code.
Right-sized stories:
- Add a database column and migration
- Add a UI component to an existing page
- Update a server action with new logic
- Add a filter dropdown to a list
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.
- 2mo ago First seen · 334 lines · 47 tokens per session scan A c7abca0a9e47
prd-converter is a skill published in the GitHub repository YougLin-dev/Aha-Loop (178 stars, last pushed 9mo ago), licensed MIT. It adds 47 tokens to every session and 2,498 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.
prd-converter compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| prd-converterYougLin-dev/Aha-Loop | Skill | 178 | 9mo ago | MIT | A | 47 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 103 | Claude Code |