web-search-opencode

web-search-opencode is an agent for coding agents from Weizhena/Deep-Research-skills. It costs 62 tokens per session (1,557 once invoked), scanned A, a copy of web-search-agent, MIT.

An internet-research agent for investigating technical problems and collecting information from sources such as documentation, forums, research sites, and developer communities.

In plain words
What is it for?
Use it to research bugs, compare technical solutions, and find information across multiple online sources.
Why use it?
It helps gather relevant discussions and possible solutions when a quick search does not provide enough context.

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 · 2,098 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.

agentmods
npx agentmods add agents/weizhena/deep-research-skills/web-search-opencode
Clone the repo
git clone --depth 1 https://github.com/Weizhena/Deep-Research-skills

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-opencode

README.md
[![agentmods](https://agentmods.dev/badge/agents/weizhena/deep-research-skills/web-search-opencode.svg)](https://agentmods.dev/agents/weizhena/deep-research-skills/web-search-opencode)
Your own site
<a href="https://agentmods.dev/agents/weizhena/deep-research-skills/web-search-opencode"><img src="https://agentmods.dev/badge/agents/weizhena/deep-research-skills/web-search-opencode.svg" alt="Measured on agentmods" height="20"></a>
Per session 62 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,557 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 88% copy Near-identical to another mod 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 $0.00062 $0.01557
Opus 5 $0.00031 $0.00779
Sonnet 5 $0.00012 $0.00311
Haiku 4.5 $0.00006 $0.00156

Measured 5d ago against content hash 6c365611a47a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

web-search-opencode 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 5d 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.

Origin

This is a copy

88% identical to web-search-agent — 20 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

agents/web-search-opencode.md · 138 lines

How it starts

The opening of the file, as written. The whole thing — 138 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 ~/.config/opencode/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 · 138 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. 5d ago First seen · 138 lines · 62 tokens per session scan A 6c365611a47a

Subscribe to this mod's changes

web-search-opencode is an agent published in the GitHub repository Weizhena/Deep-Research-skills (2,098 stars, last pushed 13d ago), licensed MIT. It adds 62 tokens to every session and 1,557 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to web-search-agent, differing in 20 lines, and is treated as a copy.

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