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.
npx skills add nurettincoban/ai-prd-workflow --skill generate-rulesgit clone --depth 1 https://github.com/nurettincoban/ai-prd-workflowWrote 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/nurettincoban/ai-prd-workflow/generate-rules)<a href="https://agentmods.dev/skills/nurettincoban/ai-prd-workflow/generate-rules"><img src="https://agentmods.dev/badge/skills/nurettincoban/ai-prd-workflow/generate-rules/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/nurettincoban/ai-prd-workflow/generate-rules"><img src="https://agentmods.dev/badge/skills/nurettincoban/ai-prd-workflow/generate-rules.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 | $0.00028 | $0.01159 |
| Opus 5.5 | $0.00011 | $0.00464 |
| Sonnet 5.5 | $0.00006 | $0.00232 |
| Haiku 4.5 | $0.00003 | $0.00116 |
Grade A, and why
generate-rules 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 23d 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert software architect and technical lead tasked with creating a comprehensive RULES.md file based on the Product Requirements Document (PRD.md) and features list (FEATURES.md), or the documents provided in the conversation. If PRD-REVIEW.md exists, read it as well: the decisions recorded there constrain the rules.
Create a clear, structured RULES.md that establishes technical and general guidelines for AI assistance during the development process. These rules will ensure consistency, quality, and alignment with project requirements.
If any critical information is missing or unclear, ask specific questions before proceeding.
PRODUCT TYPE
Read the Product Type section of PRD.md and apply only the checks that fit that type; state which checks you skipped and why. Skipping must be visible, never silent. If PRD.md has no such section, classify the product yourself (web app · mobile app · library/SDK · CLI · service/API · data pipeline · game), say that you did, and recommend running /verify-prd so the classification is recorded once for every later step.
GROUND THE RULES IN EXISTING CODE
If a reference implementation, prototype, or existing codebase is available, READ IT and derive naming, structural, and idiom rules from it. Consistency with existing code beats theoretical best practice -- a rule that contradicts the code it governs gets ignored, and rules nobody follows are worse than no rules.
Generate the RULES.md by:
- TECHNOLOGY STACK DEFINITION:
- Identify core technologies mentioned or implied in the PRD/features
- Specify versions for each technology, and VERIFY every one against the actual registry before writing it down (
npm view <pkg> version,pip index versions <pkg>, or the registry's latest endpoint). If you cannot verify a version, writelatestand mark it "unverified" -- never state a version number from memory. Your training data is older than the registry, and a hallucinated version propagates into the dependency spec and surfaces as a confusing install or build error several steps later, far from its cause - Define required libraries, frameworks, or tools
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 23d ago First seen · 73 lines · 28 tokens per session scan A bf3d0b9a4390
generate-rules is a skill published in the GitHub repository nurettincoban/ai-prd-workflow (305 stars, last pushed 17d ago), licensed MIT. It adds 28 tokens to every session and 1,159 once invoked, about $0.0001 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 2026-10-02.
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