
Deep Research
- 1.6k installs
- 238k repo stars
- Updated August 5, 2026
- affaan-m/ecc
This is a copy of deep-research by affaan-m - installs and ranking accrue to the original listing.
deep-research is an ECC agent skill that produces multi-source cited research reports using Firecrawl and Exa MCP tools for developers who need evidence-backed answers before technical or business decisions.
About
deep-research is an ECC (Everything Claude Code) skill that produces thorough, cited research reports from multiple web sources. It activates Firecrawl and Exa MCP tools to search, crawl, and synthesize findings with source attribution. Use cases include competitive analysis, technology evaluation, market sizing, and due diligence on companies or investors. Developers reach for deep-research when a question needs synthesis across sources rather than a single documentation lookup. Trigger phrases include research, deep dive, investigate, and what's the landscape. Output is a structured report with citations agents and humans can verify.
- Multi-source web research combining Firecrawl and Exa MCP servers
- Synthesizes findings into cited reports with source attribution
- Activates on triggers like 'research', 'deep dive', 'investigate', or 'current state of'
- Supports competitive analysis, technology evaluation, market sizing, and due diligence
- Requires at least one of Firecrawl or Exa MCP tools configured
Deep Research by the numbers
- 1,599 all-time installs (skills.sh)
- +109 installs in the week ending Aug 5, 2026 (Skillselion tracking)
- Security screen: MEDIUM risk (skills.sh audit)
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 1.6k |
|---|---|
| repo stars | ★ 238k |
| Security audit | 2 / 3 scanners passed |
| Last updated | August 5, 2026 |
| Repository | affaan-m/ecc ↗ |
How do agents produce cited multi-source research reports?
Generate thorough, multi-source cited research reports on any topic using Firecrawl and Exa MCP tools.
Who is it for?
Developers and technical leads who need agent-driven competitive analysis, technology evaluation, or due diligence with verifiable citations.
Skip if: Tasks that only need a single API doc lookup, private codebase analysis, or real-time production monitoring without web research.
When should I use this skill?
A user asks to research a topic in depth, run a competitive analysis, or investigate a technology with citations and multiple sources.
What you get
Cited research reports, source-attributed summaries, and synthesized findings from multiple web pages.
- Cited research report
- Source-attributed summary
By the numbers
- Integrates 2 MCP research tools: Firecrawl and Exa
Files
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:
# [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 themesEach 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"interface:
display_name: "Deep Research"
short_description: "Multi-source cited research reports"
brand_color: "#6366F1"
default_prompt: "Use $deep-research to produce a cited multi-source research report."
policy:
allow_implicit_invocation: true
Related skills
How it compares
Use deep-research when answers must combine multiple live web sources with citations instead of relying on the model's training data alone.
FAQ
Which MCP tools does deep-research use?
deep-research uses Firecrawl and Exa MCP tools to search the web, crawl pages, and gather sources. Findings are synthesized into a cited report with attribution for each claim.
When should deep-research activate?
deep-research activates when a user requests thorough research, competitive analysis, technology evaluation, market sizing, or due diligence and needs evidence from multiple web sources.
Is Deep Research safe to install?
skills.sh reports 2 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.