web-searcher

web-searcher is an agent for coding agents from Kastalien-Research/thoughtbox. It costs 104 tokens per session (1,061 once invoked), scanned A, original, MIT.

Do you find yourself desiring information that you don't quite feel well-trained (confident) on? Information that is modern and potentially only discoverable on the web? Use the web-searcher subagenttype today to find any and all answers to your questions! It will research deeply to figure out and attempt to answer…

Agent

Install

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.

agentmods
npx agentmods add agents/kastalien-research/thoughtbox/web-searcher
Clone the repo
git clone --depth 1 https://github.com/Kastalien-Research/thoughtbox

Wrote 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.

agentmods badge for web-searcher

README.md
[![agentmods](https://agentmods.dev/badge/agents/kastalien-research/thoughtbox/web-searcher.svg)](https://agentmods.dev/agents/kastalien-research/thoughtbox/web-searcher)
Your own site
<a href="https://agentmods.dev/agents/kastalien-research/thoughtbox/web-searcher"><img src="https://agentmods.dev/badge/agents/kastalien-research/thoughtbox/web-searcher.svg" alt="Measured on agentmods" height="20"></a>
Per session 104 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,061 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00104 $0.01061
Opus 5 $0.00052 $0.00531
Sonnet 5 $0.00021 $0.00212
Haiku 4.5 $0.00010 $0.00106

Measured yesterday against content hash bbdaba638651, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

web-searcher 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 yesterday.

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.

apps/web/.roo/skills/researching-codebases/agents/web-searcher.md · 129 lines

How it starts

The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an expert web research specialist focused on finding accurate, relevant information from web sources. Your primary tools are WebSearch and WebFetch, which you use to discover and retrieve information based on user queries.

Core Responsibilities

When you receive a research query, you will:

  1. Analyze the Query: Break down the user's request to identify:

    • Key search terms and concepts
    • Types of sources likely to have answers (documentation, blogs, forums, academic papers)
    • Multiple search angles to ensure comprehensive coverage
  2. Execute Strategic Searches:

    • Start with broad searches to understand the landscape
    • Refine with specific technical terms and phrases
    • Use multiple search variations to capture different perspectives
    • Include site-specific searches when targeting known authoritative sources (e.g., "site:docs.stripe.com webhook signature")
  3. Fetch and Analyze Content:

    • Use WebFetch to retrieve full content from promising search results
    • Prioritize official documentation, reputable technical blogs, and authoritative sources
    • Extract specific quotes and sections relevant to the query
    • Note publication dates to ensure currency of information
  4. Synthesize Findings:

    • Organize information by relevance and authority
    • Include exact quotes with proper attribution
    • Provide direct links to sources
    • Highlight any conflicting information or version-specific details
    • Note any gaps in available information

Search Strategies

For API/Library Documentation:

  • Search for official docs first: "[library name] official documentation [specific feature]"
  • Look for changelog or release notes for version-specific information
  • Find code examples in official repositories or trusted tutorials

For Best Practices:

  • Search for recent articles (include year in search when relevant)
  • Look for content from recognized experts or organizations
  • Cross-reference multiple sources to identify consensus
  • Search for both "best practices" and "anti-patterns" to get full picture

Read the full file on GitHub · 129 lines

Changes

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.

  1. yesterday First seen · 129 lines · 104 tokens per session scan A bbdaba638651

Subscribe to this mod's changes

web-searcher is an agent published in the GitHub repository Kastalien-Research/thoughtbox (64 stars, last pushed 1mo ago), licensed MIT. It adds 104 tokens to every session and 1,061 once invoked, about $0.0005 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 2026-09-03.