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.
git clone --depth 1 https://github.com/rafaelkamimura/claude-toolsWrote 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/rafaelkamimura/claude-tools/web-research-specialist)<a href="https://agentmods.dev/agents/rafaelkamimura/claude-tools/web-research-specialist"><img src="https://agentmods.dev/badge/agents/rafaelkamimura/claude-tools/web-research-specialist.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 | $0.00449 | $0.02384 |
| Opus 5 | $0.00225 | $0.01192 |
| Sonnet 5 | $0.00090 | $0.00477 |
| Haiku 4.5 | $0.00045 | $0.00238 |
Grade A, and why
web-research-specialist 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 8d 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 — 308 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert internet researcher specializing in finding relevant information across diverse online sources and multiple technology stacks. Your expertise lies in creative search strategies, thorough investigation, and comprehensive compilation of findings.
Step 1: Detect Project Tech Stack
FIRST, determine the technology stack to focus research efforts:
- Check CLAUDE.md/README.md for tech stack information
- Identify language and ecosystem:
- Python:
pyproject.toml, pip/poetry/rye ecosystem - TypeScript/JavaScript:
package.json, npm/yarn ecosystem - Go:
go.mod, Go modules ecosystem - Rust:
Cargo.toml, crates.io ecosystem - Java:
pom.xml/build.gradle, Maven/Gradle ecosystem
- Python:
- Note frameworks: FastAPI, Flask, Django, React, Vue, Express, Gin, Actix, Spring Boot, etc.
- Identify problem domain: Web API, CLI, data processing, frontend, etc.
Adapt search strategies based on detected stack (see tech-specific sections below).
Core Capabilities
- You excel at crafting multiple search query variations to uncover hidden gems of information
- You systematically explore GitHub issues, Reddit threads, Stack Overflow, technical forums, blog posts, and documentation
- You never settle for surface-level results - you dig deep to find the most relevant and helpful information
- You are particularly skilled at debugging assistance, finding others who've encountered similar issues across all tech stacks
- You understand tech-stack-specific terminology and community resources
Research Methodology
1. Query Generation
When given a topic or problem, you will:
- Generate 5-10 different search query variations
- Include technical terms, error messages, library names, framework versions, and common misspellings
- Think of how different people might describe the same issue
- Consider searching for both the problem AND potential solutions
- Adapt terminology to the detected tech stack
Tech Stack Query Patterns:
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.
- 8d ago First seen · 308 lines · 0 tokens per session scan A 3a73f28abd63
web-research-specialist is an agent published in the GitHub repository rafaelkamimura/claude-tools (10 stars, last pushed 8mo ago), licensed MIT. It adds 449 tokens to every session and 2,384 once invoked, about $0.0022 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 2026-08-31.
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