agent-deep-research
Autonomous deep research powered by Google Gemini.
Best use case
agent-deep-research is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Autonomous deep research powered by Google Gemini.
Teams using agent-deep-research should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/agent-deep-research/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How agent-deep-research Compares
| Feature / Agent | agent-deep-research | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Autonomous deep research powered by Google Gemini.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
# agent-deep-research Autonomous deep research powered by Google Gemini. ## Install ``` npx clawhub@latest install agent-deep-research ```
Related Skills
academic-deep-research
Transparent, rigorous research with full methodology — not a black-box API wrapper. Conducts exhaustive investigation through mandated 2-cycle research per theme, APA 7th citations, evidence hierarchy, and 3 user checkpoints. Self-contained using native OpenClaw tools (web_search, web_fetch, sessions_spawn). Use for literature reviews, competitive intelligence, or any research requiring academic rigor and reproducibility.
research-tracker
Manage autonomous AI research agents with SQLite-based state tracking. Use when spawning long-running research sub-agents, tracking multi-step investigations, coordinating agent handoffs, or monitoring background work. Triggers on: research projects, sub-agent coordination, autonomous investigation, progress tracking, agent oversight.
yutori-web-research
Use Yutori’s Research API and Browsing API (cloud browser) to research topics, collect sources, and extract structured facts from the web. Use when the user asks to “research X”, “monitor/find papers”, or “navigate to a site and extract info” and you have access to YUTORI dev/prod endpoints via YUTORI_API_BASE and an API key in env (YUTORI_API_KEY or ~/.openclaw/openclaw.json env.YUTORI_API_KEY).
research-library
Local-first multimedia research library for hardware projects.
research-assistant
Organized research and knowledge management for agents.
market-research-2
Conduct structured market research for a solopreneur business.
deep-research
Comprehensive research framework that combines web search, content analysis, source verification, and iterative investigation to conduct in-depth research on any topic. Use when you need to perform thorough research with multiple sources, cross-validation, and structured findings.
focus-deep-work
Maximize deep work with focus sessions, distraction logging, and productivity tracking
research-paper-kb
Persistent cross-session knowledge base for research papers.
perplexity-research
Conduct deep research using Perplexity Agent API with web search, reasoning, and multi-model analysis.
research-report
Research technical projects/papers and generate comprehensive reports with PDF export.
reddit-nlp-research-problems
Discussion on important NLP research problems in academia and industry. Use when exploring current challenges in natural language processing, low-resource language models, or conversational AI research directions.