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-implement/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-implement)<a href="https://agentmods.dev/skills/wirasm/prp/prp-implement"><img src="https://agentmods.dev/badge/skills/wirasm/prp/prp-implement/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-implement"><img src="https://agentmods.dev/badge/skills/wirasm/prp/prp-implement.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 | $0.00080 | $0.04106 |
| Opus 5.5 | $0.00032 | $0.01642 |
| Sonnet 5.5 | $0.00016 | $0.00821 |
| Haiku 4.5 | $0.00008 | $0.00411 |
Grade A, and why
prp-implement 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 17d 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 — 199 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.
Implement Plan
Execute the supplied implementation plan through a validated commit and pull request, or apply review findings to that pull request. Keep implementation, commit, and PR delivery in this context; leave review judgment to its own context.
Input: $ARGUMENTS
Mode
- A plan path starts the initial implementation.
- A change its caller judged tiny work, such as
$prp-issue's tiny route, starts the initial implementation with no plan. The change description is the contract. Write no implementation report; the PR description carries the problem, the fix, and the evidence. Wherever a later step records something in the report, tiny work puts it in the PR description, or in the returned result before a PR exists; a blocked tiny change returnsVALIDATION: FAILEDwith the blocker. If the change turns out not to be tiny, stop before committing and return that, so the caller plans it. reviewplus a review report, PR, or finding decisions starts a correction pass. Resolve and read the original plan, implementation report, live PR diff and comments, complete canonical review report, and any explicit finding dispositions before editing. Human dispositions are binding when supplied. Otherwise resolve every finding by judgment: Critical or Important findings require correction or an evidence-backed disagreement, and for the rest, fix what matters now, including adjacent findings, track only real work unrelated to the change, fix taste that fits the project's direction and engineering docs, and decline other taste or wrong findings with a reason.ciplus a PR and failing-check evidence starts a correction pass. Resolve the original plan, implementation report, live PR diff, complete check status and logs, and reproduce the failure before editing. Correct only PR-caused failures; preserve evidence when the failure is external or pre-existing.
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.
- 17d ago Changed · +32 lines a3b71b20b136
- 18d ago Changed · +30 lines 02fad4282adc
- 23d ago Changed dc31f0340396
- 1mo ago First seen · 137 lines · 80 tokens per session scan A 035c637bfc49
prp-implement is a skill published in the GitHub repository Wirasm/prp (2,264 stars, last pushed 18d ago), licensed MIT. It adds 80 tokens to every session and 4,106 once invoked, about $0.0003 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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