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.
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 agentmods add skills/wirasm/prp/prp-meta-skillnpx skills add Wirasm/prp --skill prp-meta-skillgit 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-meta-skill)<a href="https://agentmods.dev/skills/wirasm/prp/prp-meta-skill"><img src="https://agentmods.dev/badge/skills/wirasm/prp/prp-meta-skill.svg" alt="Measured on agentmods" 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 | $0.00080 | $0.01579 |
| Opus 5 | $0.00040 | $0.00790 |
| Sonnet 5 | $0.00016 | $0.00316 |
| Haiku 4.5 | $0.00008 | $0.00158 |
Grade A, and why
prp-meta-skill 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 5d 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PRP Meta-Skill — Author, Refactor & Consolidate Skills
A PRP-style runbook for three jobs:
- Create a new skill from scratch (or from an existing command/prompt).
- Refactor an existing skill — split detail into
references/, move output formats intotemplates/, and trimSKILL.mdto a lean spine of pointers. - Consolidate overlapping workflows — trace their contracts, choose one composition owner, reuse specialist skills, and retire duplicate paths without losing outcomes or human gates.
This skill is built the way it teaches: a lean body that defers detail to references/. Follow that example.
Prescribe the craft, not the content
This skill is opinionated about how to build a skill well and deliberately agnostic about what any given skill — or the artifact it produces — should contain.
- Prescribe (firm, universal): progressive disclosure, third-person trigger-rich descriptions, imperative body, no-duplication, lean body, every reference wired, deliberate invocation control, validation that fits. See
references/skill-standards.md. - Do NOT prescribe (per-project, the author's call): the sections a plan / PRD / report should contain, what a project's template looks like, which phases exist, the domain vocabulary. There is no canonical output shape — guide the author to a good decision, never hand them a fixed one.
Restrictions are not rigidity: be strict on the craft so the author stays free on the content.
The PRP lens — applied to the skill type
Classify the skill first (workflow / artifact-generator / knowledge-reference / tool-wrapper — see references/skill-standards.md → Skill types), then apply only the principles that fit:
- Context is King — give the agent ALL the context it needs (patterns, gotchas, schemas, examples) via whichever source fits: inline, bundled and disclosed on demand, pointed to by file path or URL, or gathered from the user at runtime. Curate it — don't dump it. (
references/skill-standards.md→ Context sources.) - Validation that fits — workflow skills ship verifiable gates, and prefer an external, authoritative check (exit code, file presence) over the agent's own "done" sentinel. A knowledge/reference skill has nothing to validate — don't bolt a loop onto it.
- Information dense — real trigger phrases, real examples, real
file:line. No filler, no restating what the model already knows. - Progressive success — ship the smallest complete SKILL.md that triggers correctly first, validate, then enrich with references. Don't build all the references before the spine works.
What ships with it
7 files 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.
- 5d ago First seen · 78 lines · 80 tokens per session scan A 3f8c007fde46
prp-meta-skill is a skill published in the GitHub repository Wirasm/prp (2,242 stars, last pushed 4d ago), licensed MIT. It adds 80 tokens to every session and 1,579 once invoked, about $0.0004 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…