deep-research
Skill0 starsChanged 4 months agoMITView on GitHub
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.
We split this skill into the rules it gives an agent
9 rules. 0 are common, 9 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 176 edited versions we read keep these.
9
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 36
Ask 1-2 quick clarifying questions:
- Distinctive: line 40
If the user says "just research it" — skip ahead with reasonable defaults.
- Distinctive: line 68
Use 2-3 different keyword variations per sub-question
- Distinctive: line 87
Read 3-5 key sources in full for depth.
- Distinctive: line 145
Every claim needs a source: No unsourced assertions.
- Distinctive: line 146
Cross-reference: If only one source says it, flag it as unverified.
- Distinctive: line 147
Recency matters: Prefer sources from the last 12 months.
- Distinctive: line 148
Acknowledge gaps: If you couldn't find good info on a sub-question, say so.
- Distinctive: line 149
No hallucination: If you don't know, say "insufficient data found."
“Common” is measured: kept by at least 6 in 10 of the 176 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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:
# [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
- Every claim needs a source. No unsourced assertions.
- Cross-reference. If only one source says it, flag it as unverified.
- Recency matters. Prefer sources from the last 12 months.
- Acknowledge gaps. If you couldn't find good info on a sub-question, say so.
- No hallucination. If you don't know, say "insufficient data found."
- 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"Other versions196 projects use a version of this.
Word for word · 1
- gongyijie85/dsh-ecc★ 8100% same
Edited · 18
- affaan-m/ECC★ 246k99% same
- loulanyue/awesome-claude-notes★ 27299% same
- tpavanipradeep/everything-claude-code★ 10499% same
- mturac/everything-openai-codex★ 8997% same
- mit-network/everything-claude-code★ 7699% same
- Fmarzochi/EGC★ 6198% same
- ysyecust/everything-claude-code★ 4499% same
- woxiangyangzhimao/skills★ 1498% same
- EthanYoQ/Skill-hub★ 1179% same
- VoVuongThanhDat/agentflow★ 899% same
8 more not listed
Wrote their own version · 177
- bytedance/deer-flow★ 85ksame name
- Imbad0202/academic-research-skills★ 55ksame name
- THU-MAIC/OpenMAIC★ 42ksame name
- genspark-ai/genoffice★ 11ksame name
- HKUSTDial/Supervisor-Skills★ 11ksame name
- getcompanion-ai/feynman★ 10ksame name
- advaitpaliwal/feynman★ 10ksame name
- companion-inc/feynman★ 10ksame name
- jordan-gibbs/hyperresearch★ 4.2ksame name
- davidondrej/skills★ 4.2ksame name
167 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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