deep-research

Generates cited multi-source research reports using firecrawl and exa web search MCPs.

Updated Mar 22, 2026
One-click install
npx skills add https://github.com/diazMelgarejo/orama-system --skill deep-research-diazmelgarejo
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: deep-research
Source: https://github.com/diazMelgarejo/orama-system/tree/main/.cursor/.agents/skills/deep-research
Command: npx skills add https://github.com/diazMelgarejo/orama-system --skill deep-research-diazmelgarejo

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Answering complex questions requires gathering, reading, and synthesizing information from many web sources, which is slow and error-prone when done manually. This Skill automates multi-source web research and delivers structured reports where every claim is backed by a cited source. ## Core Features & Use Cases - Multi-Source Search: Breaks a topic into 3-5 sub-questions and searches each with firecrawl and exa MCP tools, targeting 15-30 unique sources. - Deep Source Reading: Fetches full content of key sources via firecrawl_scrape or crawling_exa instead of relying on search snippets. - Cited Report Generation: Produces a structured report with executive summary, themed sections, inline citations, key takeaways, and a source list. - Parallel Research: Supports launching parallel subagents to research sub-questions concurrently for broad topics. - Use Case: Ask for a deep dive into the competitive landscape for AI code editors and receive a report with sourced findings, market context, and clearly labeled confidence levels. ## Quick Start Ask the agent to research the current state of nuclear fusion energy and deliver a cited report.

Frequently Asked Questions about deep-research

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I do deep web research with cited sources using AI?▼

Break the topic into 3-5 sub-questions, search each with firecrawl or exa MCP tools, read the top sources in full, then synthesize findings into a report with inline citations and a source list. This Skill automates that entire workflow.

What MCP tools are needed for multi-source web research?▼

At least one of firecrawl (firecrawl_search, firecrawl_scrape, firecrawl_crawl) or exa (web_search_exa, web_search_advanced_exa, crawling_exa) is required. Using both together gives the best source coverage.

How do I configure firecrawl or exa for research?▼

Configure the MCP servers in ~/.claude.json or ~/.codex/config.toml with your API credentials. Once configured, the Skill can call their search and crawl tools directly during research.

Can research tasks be parallelized across multiple agents?▼

Yes. For broad topics, the Skill uses Claude Code's Task tool to launch parallel research agents, each handling different sub-questions. The main session then synthesizes their findings into the final report.

How does the research report handle unverified or missing information?▼

Claims supported by only one source are flagged as unverified, and sub-questions with insufficient data are explicitly acknowledged as gaps. Estimates and opinions are labeled separately from facts.