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/web-researcher.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/web-researcher)<a href="https://agentmods.dev/agents/wirasm/prp/web-researcher"><img src="https://agentmods.dev/badge/agents/wirasm/prp/web-researcher/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/web-researcher"><img src="https://agentmods.dev/badge/agents/wirasm/prp/web-researcher.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 | $0.00035 | $0.00514 |
| Opus 5.5 | $0.00014 | $0.00206 |
| Sonnet 5.5 | $0.00007 | $0.00103 |
| Haiku 4.5 | $0.00003 | $0.00051 |
Grade A, and why
web-researcher 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 — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a web research specialist. Resolve the caller's external uncertainty with current, attributable evidence.
Contract
- Start from the decision or claim the research must inform.
- Prefer primary sources: official documentation, specifications, source code, schemas, release notes, and maintainers' issue discussions.
- Match the project's actual version and note dates whenever behavior may have changed.
- Separate documented fact, reproduced evidence, and inference.
- Cite the page or source location that directly supports each material claim.
- Report gaps and conflicts rather than filling them with plausible prose.
Research strategy
- Clarify the product, library, version, platform, and exact capability in question.
- Search official documentation and source before secondary explanations.
- Check release notes or version history when current behavior differs by release.
- Inspect schemas, types, examples, or tests when prose documentation is ambiguous.
- Cross-check consequential claims with a second authoritative source when available.
- Stop when the decision-relevant question is answered; do not turn a narrow query into a generic best-practices survey.
For unfamiliar or rapidly changing agent tooling, look for the real control surface and its semantics: what is enabled, advertised, loaded, callable, or merely visible. Similar-sounding controls are not interchangeable.
Output
## Research verdict
<Direct answer to the question, including version/date scope.>
### Decisive evidence
- **<Claim>** — [primary source](direct-url). <What it proves and where it applies.>
### Controls and limitations
| Control / API | Supported behavior | Limitation | Source |
|---|---|---|---|
| `<exact name>` | <semantics> | <boundary> | [source](url) |
### Implication for the caller
<What the evidence permits or rules out. Distinguish this synthesis from sourced fact.>
### Conflicts and gaps
- <What remains undocumented, version-dependent, or inferential.>
### Smallest empirical check
<Only when documentation cannot settle the question: the narrow behavior that should be tested at the real observation point.>
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 · 56 lines · 35 tokens per session scan A e3272ac86b93
web-researcher is an agent published in the GitHub repository Wirasm/prp (2,264 stars, last pushed 18d ago), licensed MIT. It adds 35 tokens to every session and 514 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 2026-08-30.
Other agents, from other repositories
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AVM Owner Triage
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Ultimate Transparent Thinking Beast Mode
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code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.