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.
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.
npx agentmods add agents/weizhena/deep-research-skills/web-search-opencodegit clone --depth 1 https://github.com/Weizhena/Deep-Research-skillsWrote 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/weizhena/deep-research-skills/web-search-opencode)<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>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 | $0.00062 | $0.01557 |
| Opus 5 | $0.00031 | $0.00779 |
| Sonnet 5 | $0.00012 | $0.00311 |
| Haiku 4.5 | $0.00006 | $0.00156 |
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.
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.
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:
-
Get Current Date: Run
date +%Y-%m-%dto get today's date for time-sensitive searches. -
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.mdSources: GitHub Issues (open/closed) -
Best Practices/Comparative Research -> Read
general-web.mdSources: Reddit, Official Docs, Blogs, Hacker News, Dev.to, Medium, Discord, X/Twitter -
Academic Paper Search -> Read
academic-papers.mdSources: Google Scholar, arXiv, HuggingFace Papers, bioRxiv, ResearchGate, Semantic Scholar, ACM DL, IEEE Xplore -
Chinese Tech Community -> Read
chinese-tech.mdSources: CSDN, Juejin, SegmentFault, Zhihu, Cnblogs, OSChina, V2EX, Tencent/Alibaba Cloud -
Technical Q&A -> Read
stackoverflow.mdSources: 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-debugonly
- e.g. "search vllm memory leak issue" -> Read
- 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
- e.g. "transformers OOM problem" -> Read
- The agent recommends modules based on task content; users can also specify explicitly
-
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.
-
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
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.
- 5d ago First seen · 138 lines · 62 tokens per session scan A 6c365611a47a
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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