deep-research

What this skill does

When applied, it prepends a system prompt before your request is sent — no extra calls and no change to how you are billed beyond the added tokens.

---
name: deep-research
description: 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.
---

# 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: "

Use this skill

{
  "model": "gpt-4o-mini",
  "skill": "imp-c30cb5a5-59f1-4784-8fb1-ddd3d070d218",
  "messages": [{ "role": "user", "content": "…" }]
}

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