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/.claude/agents/code-simplifier.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/agents/wirasm/prp/code-simplifier)<a href="https://agentmods.dev/agents/wirasm/prp/code-simplifier"><img src="https://agentmods.dev/badge/agents/wirasm/prp/code-simplifier/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/agents/wirasm/prp/code-simplifier"><img src="https://agentmods.dev/badge/agents/wirasm/prp/code-simplifier.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 | $0.00076 | $0.00748 |
| Opus 5.5 | $0.00030 | $0.00299 |
| Sonnet 5.5 | $0.00015 | $0.00150 |
| Haiku 4.5 | $0.00008 | $0.00075 |
Grade A, and why
code-simplifier 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Simplify Changed Code
Writing code is cheap; maintaining it and recovering option value are not. Review whether the change delivers its required outcome through the smallest coherent structure. Preserve meaningful invariants, supported behavior, and useful foundations—not accidental implementation shape.
Establish the contract
Start with the actual diff against its base. Establish the intended outcome and invariants from the request, PR, plan, changed files, tests, and direct consumers. Read beyond the diff only as needed to settle a concrete question. Existing code is evidence, not a mandate.
Test the structural decisions
Look first for decisions that add coordination or prematurely close options:
- Data shape and ownership: Do core types match the dominant access paths? Is data copied, flattened, rebuilt, cached, or represented more than once when one owner could carry it?
- Coherent capability: Does the change deepen one useful abstraction, or spread special-case coordination across callers, layers, and schemas?
- Concurrency: If another actor changes shared state concurrently, is the answer safely “nothing”? If not, should the state be isolated instead of synchronized?
- Foundations: Would one smaller primitive make the downstream logic obvious? Remove dead weight before adding scaffold; add scaffold early only when every later phase benefits from it.
- Premature machinery: Which real supported variation requires each new state, lifecycle, wrapper, configuration surface, fallback, or extension point?
Apply the laziness test:
- Prefer deletion and direct control flow before introducing helpers or abstractions.
- Keep call paths flat enough that ownership and decisions remain easy to trace. A rich interface that hides substantial work is not itself a deep call chain.
- Consolidate each decision behind one source of truth and pass the resolved result plainly.
- Question new signals threaded through types, schemas, pipelines, or layers; look for the owner or primitive that already knows the answer.
- Catch small pass-throughs, representation leaks, and duplicated choices before they become lasting coordination costs.
- DRY shared structure and data models, not every repeated line. Explicit repetition can be simpler than a premature abstraction.
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 · 67 lines · 76 tokens per session scan A 0f0103c9c0f5
code-simplifier is an agent published in the GitHub repository Wirasm/prp (2,264 stars, last pushed 18d ago), licensed MIT. It adds 76 tokens to every session and 748 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.
Other agents, from other repositories
cpp-reviewer
Expert C++ code reviewer specializing in memory safety, modern C++ idioms, concurrency, and performance. Use for all C++ code changes. MUST BE USED for C++ projects.
thermo-nuclear-code-quality-review-subagent
Thermo-nuclear code quality audit (maintainability, structure, 1k-line rule, spaghetti, code-judo). Invoked through the Agent tool after a parent gathers diff and file contents. Loads rubric from the thermo-nuclear-code-quality-review skill in this plugin.
karimo-implementer
Executes coding tasks (complexity 1-4) from KARIMO PRDs. Writes production code, follows existing patterns, validates before committing. Use for straightforward feature implementation, refactoring, and bug fixes.
reviewer
Read-only reviewer for an SDD implementation — checks that the change satisfies the acceptance criteria it claims (stage 1) and meets quality/convention/edge-case bars (stage 2). Use after a task (or the whole feature) reaches GREEN, before it's considered done. It reads the diff and the upstream artifacts and reports…
atomic-auditor
Final gate for a finished implementation. Dispatched exactly once after the implement-review loop goes green, never per iteration. Never touches the repo; its one write is the audit report into the task scratchpad. Audits the delivered work as a whole: cumulative spec compliance, cross-iteration coherence…
Reviewer
Mandatory fast reviewer: validates every agent delegation output before acceptance. Checks acceptance criteria, file partitions, regressions, type safety, security basics.