deep-research
Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any topic with evidence and citations.
Best use case
deep-research is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any topic with evidence and citations.
Teams using 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/deep-research/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How deep-research Compares
| Feature / 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?
Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any topic with evidence and citations.
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.
SKILL.md Source
# Deep Research Produce thorough, cited research reports from multiple web sources using firecrawl and exa MCP tools. ## When to Activate - User asks to research any topic in depth - Competitive analysis, technology evaluation, or market sizing - Due diligence on companies, investors, or technologies - Any question requiring synthesis from multiple sources - User says "research", "deep dive", "investigate", or "what's the current state of" ## MCP Requirements At least one of: - **firecrawl** — `firecrawl_search`, `firecrawl_scrape`, `firecrawl_crawl` - **exa** — `web_search_exa`, `web_search_advanced_exa`, `crawling_exa` Both together give the best coverage. Configure in `~/.claude.json` or `~/.codex/config.toml`. ## Workflow ### Step 1: Understand the Goal Ask 1-2 quick clarifying questions: - "What's your goal — learning, making a decision, or writing something?" - "Any specific angle or depth you want?" If the user says "just research it" — skip ahead with reasonable defaults. ### Step 2: Plan the Research Break the topic into 3-5 research sub-questions. Example: - Topic: "Impact of AI on healthcare" - What are the main AI applications in healthcare today? - What clinical outcomes have been measured? - What are the regulatory challenges? - What companies are leading this space? - What's the market size and growth trajectory? ### Step 3: Execute Multi-Source Search For EACH sub-question, search using available MCP tools: **With firecrawl:** ``` firecrawl_search(query: "<sub-question keywords>", limit: 8) ``` **With exa:** ``` web_search_exa(query: "<sub-question keywords>", numResults: 8) web_search_advanced_exa(query: "<keywords>", numResults: 5, startPublishedDate: "2025-01-01") ``` **Search strategy:** - Use 2-3 different keyword variations per sub-question - Mix general and news-focused queries - Aim for 15-30 unique sources total - Prioritize: academic, official, reputable news > blogs > forums ### Step 4: Deep-Read Key Sources For the most promising URLs, fetch full content: **With firecrawl:** ``` firecrawl_scrape(url: "<url>") ``` **With exa:** ``` crawling_exa(url: "<url>", tokensNum: 5000) ``` Read 3-5 key sources in full for depth. Do not rely only on search snippets. ### Step 5: Synthesize and Write Report Structure the report: ```markdown # [Topic]: Research Report *Generated: [date] | Sources: [N] | Confidence: [High/Medium/Low]* ## Executive Summary [3-5 sentence overview of key findings] ## 1. [First Major Theme] [Findings with inline citations] - Key point ([Source Name](url)) - Supporting data ([Source Name](url)) ## 2. [Second Major Theme] ... ## 3. [Third Major Theme] ... ## Key Takeaways - [Actionable insight 1] - [Actionable insight 2] - [Actionable insight 3] ## Sources 1. [Title](url) — [one-line summary] 2. ... ## Methodology Searched [N] queries across web and news. Analyzed [M] sources. Sub-questions investigated: [list] ``` ### Step 6: Deliver - **Short topics**: Post the full report in chat - **Long reports**: Post the executive summary + key takeaways, save full report to a file ## Parallel Research with Subagents For broad topics, use Claude Code's Task tool to parallelize: ``` Launch 3 research agents in parallel: 1. Agent 1: Research sub-questions 1-2 2. Agent 2: Research sub-questions 3-4 3. Agent 3: Research sub-question 5 + cross-cutting themes ``` Each agent searches, reads sources, and returns findings. The main session synthesizes into the final report. ## Quality Rules 1. **Every claim needs a source.** No unsourced assertions. 2. **Cross-reference.** If only one source says it, flag it as unverified. 3. **Recency matters.** Prefer sources from the last 12 months. 4. **Acknowledge gaps.** If you couldn't find good info on a sub-question, say so. 5. **No hallucination.** If you don't know, say "insufficient data found." 6. **Separate fact from inference.** Label estimates, projections, and opinions clearly. ## Examples ``` "Research the current state of nuclear fusion energy" "Deep dive into Rust vs Go for backend services in 2026" "Research the best strategies for bootstrapping a SaaS business" "What's happening with the US housing market right now?" "Investigate the competitive landscape for AI code editors" ```
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