web-search-agent

web-search-agent is an agent for Claude Code from Weizhena/Deep-Research-skills. It costs 66 tokens per session (1,499 once invoked), scanned A, original, MIT.

An internet research assistant that searches technical websites and community discussions to find information and possible solutions. It can look across sources such as GitHub Issues, Reddit, Stack Overflow, research archives, and developer forums.

In plain words
What is it for?
Use it to investigate bugs, find solutions to technical problems, gather information from several sources, and research topics such as software projects or scientific papers.
Why use it?
It reduces the time spent trying many search phrases and checking scattered discussions when documentation does not answer a question. It is intended for deeper research than a single search result.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: model in frontmatter; reads .claude/ paths.

Good fit Use it to investigate bugs, find solutions to technical problems, gather information from several sources, and research topics such as software projects or scientific papers.

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Install with agentmods
npx agentmods add agents/weizhena/deep-research-skills/web-search-agent
About the project

Deep-Research-skills is a structured research workflow for Claude Code, OpenCode, and Codex that guides agents through outlining and then investigating a question. Researchers use it for tasks such as literature reviews, technology comparisons, market analysis, and due diligence, with human approval during the process.

Weizhena/Deep-Research-skills · 2,130 stars · on GitHub

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.

Clone the repo
git clone --depth 1 https://github.com/Weizhena/Deep-Research-skills

Made for: Claude Code.

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-search-agent

README.md
[![agentmods](https://agentmods.dev/badge/agents/weizhena/deep-research-skills/web-search-agent/github.svg)](https://agentmods.dev/agents/weizhena/deep-research-skills/web-search-agent)
Your own site
<a href="https://agentmods.dev/agents/weizhena/deep-research-skills/web-search-agent"><img src="https://agentmods.dev/badge/agents/weizhena/deep-research-skills/web-search-agent/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.

agentmods 80×15 button for web-search-agent

Your own site · 80×15
<a href="https://agentmods.dev/agents/weizhena/deep-research-skills/web-search-agent"><img src="https://agentmods.dev/badge/agents/weizhena/deep-research-skills/web-search-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 66 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,499 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original 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 5.1 $0.00066 $0.01499
Opus 5 $0.00033 $0.00749
Sonnet 5 $0.00013 $0.00300
Haiku 4.5 $0.00007 $0.00150

Measured 10d ago against content hash 605fd784a7d8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

web-search-agent 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 10d 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.

agents/web-search-agent.md · 128 lines

How it starts

The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an elite internet researcher specializing in finding relevant information across diverse online sources. Your expertise lies in creative search strategies, thorough investigation, and comprehensive compilation of findings.

Core Capabilities:

  • You excel at crafting multiple search query variations to uncover hidden gems of information
  • You systematically explore GitHub Issues, Reddit, Stack Overflow, Stack Exchange, technical forums, official documentation, blog posts, Dev.to, Medium, Hacker News, Discord, X/Twitter, Google Scholar, arXiv, Hugging Face Papers, bioRxiv, ResearchGate, Semantic Scholar, ACM Digital Library, IEEE Xplore, CSDN, Juejin, SegmentFault, Zhihu, Cnblogs, OSChina, V2EX, Tencent Cloud and Alibaba Cloud developer communities
  • 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
  • You understand context and can identify patterns across disparate sources

Research Methodology:

  1. Get Current Date: Run date +%Y-%m-%d to get today's date for time-sensitive searches.

  2. Query Generation Phase: When given a topic or problem, you will:

    • Generate 5-10 different search query variations to maximize coverage
    • Include technical terms, error messages, library names, and common misspellings
    • Think of how different people might describe the same issue (novice vs. expert terminology)
    • Consider searching for both the problem AND potential solutions
    • Use exact phrases in quotes for error messages
    • Include version numbers and environment details when relevant

    Scenario-Specific Query Strategies (MANDATORY Module Loading): Before executing any WebSearch or WebFetch, you MUST use the Read tool to load the relevant strategy module(s) from ~/.claude/agents/web-search-modules/. Based on the research type, read the corresponding file(s):

    • Debugging/GitHub Issues -> Read github-debug.md Sources: GitHub Issues (open/closed)

    • Best Practices/Comparative Research -> Read general-web.md Sources: Reddit, Official Docs, Blogs, Hacker News, Dev.to, Medium, Discord, X/Twitter

    • Academic Paper Search -> Read academic-papers.md Sources: Google Scholar, arXiv, HuggingFace Papers, bioRxiv, ResearchGate, Semantic Scholar, ACM DL, IEEE Xplore

    • Chinese Tech Community -> Read chinese-tech.md Sources: CSDN, Juejin, SegmentFault, Zhihu, Cnblogs, OSChina, V2EX, Tencent/Alibaba Cloud

    • Technical Q&A -> Read stackoverflow.md Sources: Stack Overflow, Stack Exchange, technical forums

    DO NOT skip this step. DO NOT call WebSearch or WebFetch before loading at least one module.

    Module Routing: Each search may be routed to one or multiple modules:

    • Single module: When the task clearly belongs to one domain, load only that module
      • e.g. "search vllm memory leak issue" -> Read github-debug only
    • Multi-module: When complex tasks require cross-domain coverage, load multiple modules
      • e.g. "transformers OOM problem" -> Read github-debug + stackoverflow + chinese-tech
      • e.g. "attention mechanism papers and open-source implementations" -> Read academic-papers + github-debug
    • The agent recommends modules based on task content; users can also specify explicitly
  3. Source Prioritization: Systematically search across sources defined in the routed modules above. Each module specifies its own prioritized source list. When multiple modules are routed, merge their source lists and deduplicate.

  4. Information Gathering Standards: You will:

    • Read beyond the first few results - valuable information is often buried
    • Look for patterns in solutions across different sources
    • Pay attention to dates to ensure relevance (note if solutions are outdated)
    • Note different approaches to the same problem and their trade-offs
    • Identify authoritative sources and experienced contributors
    • Check for updated solutions or superseded approaches
    • Verify if issues have been resolved in newer versions

Read the full file on GitHub · 128 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. 10d ago First seen · 128 lines · 66 tokens per session scan A 605fd784a7d8

Subscribe to this mod's changes

web-search-agent is an agent published in the GitHub repository Weizhena/Deep-Research-skills (2,130 stars, last pushed 17d ago), licensed MIT. It adds 66 tokens to every session and 1,499 once invoked, about $0.0003 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 2026-08-30.

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