
Deep Research
Run multi-source web research with Firecrawl and Exa MCP tools and deliver synthesized, cited reports for product or market decisions.
Overview
deep-research is an agent skill most often used in Idea (also Validate, Launch) that runs Firecrawl and Exa MCP research and delivers multi-source cited synthesis reports.
Install
npx skills add https://github.com/affaan-m/everything-claude-code --skill deep-researchWhat is this skill?
- Uses firecrawl_search, firecrawl_scrape, firecrawl_crawl and/or Exa web_search and crawl tools
- Step 1 clarifies user goal with 1–2 questions before searching
- Designed for competitive analysis, market sizing, tech evaluation, and due diligence
- Outputs cited reports with source attribution across multiple web sources
- Drift note: verify live MCP tool names and quotas against current Firecrawl and Exa docs
Adoption & trust: 4.6k installs on skills.sh; 210k GitHub stars; 2/3 security scanners passed (skills.sh audits).
What problem does it solve?
You need trustworthy, up-to-date findings from the web but manual tab hoarding does not scale and plain chat answers lack citations.
Who is it for?
Indie builders with Firecrawl or Exa MCP configured who want competitive, market, or technology deep dives with citations.
Skip if: Offline-only research, highly regulated secrets without URL allowlists, or tasks solvable from a single known doc without web reach.
When should I use this skill?
User asks to research a topic in depth, says research, deep dive, investigate, or needs synthesis with evidence and citations.
What do I get? / Deliverables
You receive a structured research report with attributed sources after guided goal clarification and multi-tool web retrieval.
- Multi-source cited research report
- Source attribution list
- Synthesis aligned to stated user goal
Recommended Skills
Journey fit
Spans multiple journey phases - primary shelf plus alternate fits below.
Thorough cited research most often starts in Idea before committing to what to build or buy. The workflow maps to research subphase: clarify goals, search, scrape, synthesize, and attribute sources.
Where it fits
Map competitors and positioning before choosing a niche to build.
Evaluate two stack options with current docs and community signals.
Ground launch messaging and channel choices in recent market writeups.
How it compares
MCP-driven research workflow, not a static SEO keyword list generator or a single-page scrape script.
Common Questions / FAQ
Who is deep-research for?
Solo founders and developers using Claude Code or Codex with Firecrawl and/or Exa who need synthesized, cited web research for decisions or content.
When should I use deep-research?
In Idea → research for market and competitor dives; in Validate → scope for tech choices; in Launch → distribution when grounding positioning in current sources.
Is deep-research safe to install?
It enables network search via MCP; review the Security Audits panel on this Prism page and your MCP server trust before exposing credentials or internal queries.
SKILL.md
READMESKILL.md - Deep Research
# Deep Research > **Drift-prone skill.** Firecrawl/Exa MCP tool names, quotas, and result > shapes change. Verify the configured MCP tools and current API docs before > promising coverage or quoting live source counts. 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. ##