Now liveThe Skillselion MCP - thousands of ranked skills, loaded into your agent mid-task. No install.Get it →
aaaaqwq avatar

Deep Research

  • 26 installs
  • 82 repo stars
  • Updated August 2, 2026
  • aaaaqwq/claude-code-skills

deep-research is a Claude Code skill that runs multi-source web research via firecrawl and exa MCP tools and delivers cited reports with source attribution.

About

This Claude Code skill produces cited research reports by searching the web with firecrawl and exa MCP tools and synthesizing findings with source attribution. It follows a six-step workflow from clarifying the goal to writing a structured report, and can parallelize across subagents. A developer uses it for competitive analysis, technology evaluation, or any question needing multi-source evidence.

  • Multi-source web research using firecrawl and exa MCP tools with cited, attributed reports
  • Structured six-step workflow: clarify, plan sub-questions, search, deep-read, synthesize, deliver
  • Optional parallel research via Claude Code subagents plus strict every-claim-needs-a-source rules

Deep Research by the numbers

  • 26 all-time installs (skills.sh)
  • Ranked #9,643 of 16,556 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 3, 2026 (Skillselion catalog sync)
At a glance

deep-research capabilities & compatibility

Requires firecrawl and/or exa MCP tools, which may carry their own API costs

Capabilities
web research · multi source synthesis · citation generation · competitive analysis · subagent orchestration
Use cases
research · web search · web scraping
Pricing
Bring your own API key
From the docs

What deep-research says it does

Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution.
SKILL.md
npx skills add https://github.com/aaaaqwq/claude-code-skills --skill deep-research

Add your badge

Show developers this skill is listed on Skillselion. Paste this into your README.

Listed on Skillselion
Installs26
repo stars82
Last updatedAugust 2, 2026
Repositoryaaaaqwq/claude-code-skills

What it does

Run multi-source web research through firecrawl and exa MCPs and deliver a cited report with source attribution.

Who is it for?

Developers needing thorough, cited research on a topic using MCP web tools

Skip if: Users without firecrawl or exa MCP tools configured, which the skill requires

When should I use this skill?

You want an in-depth, cited research report or a competitive/technology deep dive

What you get

A structured research report with inline citations and a listed set of sources

  • Cited research report
  • Executive summary and key takeaways
  • Source list and methodology

By the numbers

  • 6-step research workflow
  • Aims for 15-30 unique sources per report
  • Breaks a topic into 3-5 sub-questions

Files

SKILL.mdMarkdownGitHub ↗

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:

  • firecrawlfirecrawl_search, firecrawl_scrape, firecrawl_crawl
  • exaweb_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:

# [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"

Related skills

FAQ

What MCP tools does it require?

At least one of firecrawl (firecrawl_search/scrape/crawl) or exa (web_search_exa, crawling_exa); both together give the best coverage.

How does it ensure quality?

Every claim needs a source, single-source claims are flagged as unverified, and recent sources are preferred.

AI & Agent Buildingresearchagents

This week in AI coding

Five minutes, every Monday - the tools, releases and tactics for developers.

unsubscribe anytime.