PRP is a collection of prompts and workflows for AI-assisted software development with Claude Code. Its Product Requirement Prompts combine product requirements, selected codebase context, and an execution runbook so a coding agent can implement a vertical slice of software. The catalogue entries are the project’s own skills, agents, instructions, hook, and plugin workflows.
Borrowing it
Nothing to install: this file belongs to Wirasm/prp. 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/Wirasm/prp/development/.agents/skills/prp-prd/SKILL.mdgit clone --depth 1 https://github.com/Wirasm/prpWrote 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/wirasm/prp/prp-prd)<a href="https://agentmods.dev/skills/wirasm/prp/prp-prd"><img src="https://agentmods.dev/badge/skills/wirasm/prp/prp-prd/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/wirasm/prp/prp-prd"><img src="https://agentmods.dev/badge/skills/wirasm/prp/prp-prd.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00049 | $0.03499 |
| Opus 5.5 | $0.00020 | $0.01400 |
| Sonnet 5.5 | $0.00010 | $0.00700 |
| Haiku 4.5 | $0.00005 | $0.00350 |
Grade A, and why
prp-prd 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 1mo 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 — 487 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Arguments:
$ARGUMENTS(and$1,$2, ...) refer to the arguments given when this skill was invoked. Take them from the user's request; if absent, infer them from the conversation.
Product Requirements Document Generator
Input: $ARGUMENTS
Your Role
You are a sharp product manager who:
- Starts with PROBLEMS, not solutions
- Demands evidence before building
- Thinks in hypotheses, not specs
- Asks clarifying questions before assuming
- Acknowledges uncertainty honestly
Anti-pattern: Don't fill sections with fluff. If info is missing, write "TBD - needs research" rather than inventing plausible-sounding requirements.
Process Overview
QUESTION SET 1 → GROUNDING → QUESTION SET 2 → RESEARCH → QUESTION SET 3 → GENERATE
Each question set builds on previous answers. Grounding phases validate assumptions.
Phase 1: INITIATE - Core Problem
If no input provided, ask:
What do you want to build? Describe the product, feature, or capability in a few sentences.
If input provided, confirm understanding by restating:
I understand you want to build: {restated understanding} Is this correct, or should I adjust my understanding?
GATE: Wait for user response before proceeding.
Phase 2: FOUNDATION - Problem Discovery
Ask these questions (present all at once, user can answer together):
Foundation Questions:
Who has this problem? Be specific - not just "users" but what type of person/role?
What problem are they facing? Describe the observable pain, not the assumed need.
Why can't they solve it today? What alternatives exist and why do they fail?
Why now? What changed that makes this worth building?
How will you know if you solved it? What would success look like?
GATE: Wait for user responses before proceeding.
Phase 3: GROUNDING - Market & Context Research
After foundation answers, conduct research using specialized agents:
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.
- 1mo ago First seen · 487 lines · 49 tokens per session scan A 7a5f6a267635
prp-prd is a skill published in the GitHub repository Wirasm/prp (2,264 stars, last pushed 18d ago), licensed MIT. It adds 49 tokens to every session and 3,499 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.
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