deep-research

name	deep-research
description	Main research automation skill. 7-step algorithm for comprehensive research with 6 research types, query planning, parallel search, extraction, synthesis, and structured reporting. Use when conducting any multi-step research task.

Deep Research

Core algorithm for comprehensive research. 7 steps, 6 research types. All calls use ~~capability with automatic fallback between providers (see CONNECTORS.md for chains).

6 Research Types

Type	Trigger Signals	Focus	Report Template
Competitive Analysis	"competitors", "vs", "compare", "alternatives"	Sites, products, prices, positioning	Comparison Table
Market Research	"market", "trends", "TAM", "forecast"	Size, growth, segments, players	Deep Research Report
Technical Audit	"architecture", "stack", "how does it work", "best practices"	Technologies, performance, patterns	Deep Research Report
Person/Company Lookup	name, company, "who is", "about company"	Biography, history, key facts	Executive Summary
Topic Deep Dive	"explain", "deep dive", "in detail", "comprehensive"	All angles, history, current state	Deep Research Report
News & Trends	"news", "latest", "recent", year/date	Events, developments, timeline	Executive Summary

7-Step Algorithm

Step 1: CLASSIFY

Determine the research type from signals in the user's query.

Input: user query
Logic: match keywords to research type (see table above)
Output: research_type + depth_level
If ambiguous: ask user to clarify

Depth levels:

Level	Queries	Pages	Description
quick	2-3	3	Quick overview
standard	4-5	5	Standard research
deep	6-7	8-10	Deep analysis

Step 2: PLAN

Form 3-7 search queries from different angles.

1. expand_query(topic) → related terms
2. Generate queries covering different angles:
   - Direct: "{topic} overview"
   - Comparison: "{topic} vs alternatives"
   - Expert: "{topic} expert analysis review"
   - Data: "{topic} statistics data 2026"
   - Trends: "{topic} trends forecast"

IMPORTANT — Named Entity Discovery:

If the query contains a specific product/project/brand/tool name, FIRST run the Exhaustive Discovery Protocol (see search-strategies skill) BEFORE general research.

Query patterns by type:

Type	Query patterns
Competitive Analysis	"{product} pricing", "{product} vs {competitor}", "{product} reviews", "{product} features comparison"
Market Research	"{industry} market size", "{industry} trends 2026", "{industry} key players", "{industry} growth forecast"
Technical Audit	"{technology} architecture", "{technology} best practices", "{technology} performance benchmarks", "{technology} documentation"
Person/Company Lookup	"{name} background", "{company} about", "{company} funding revenue", "{name} interview"
Topic Deep Dive	"{topic} explained", "{topic} history evolution", "{topic} current state", "{topic} future predictions"
News & Trends	"{topic} latest news", "{topic} recent developments", "{topic} 2026 updates"

Step 3: SEARCH

Search using ~~search / ~~batch_search with automatic fallback (see CONNECTORS.md for provider order).

1. IF named entity (product/project/brand):
   → Run Exhaustive Discovery Protocol FIRST
   → Use found URLs as primary sources

2. ~~batch_search(queries) — parallel search
   Fallback: ~~search(query) for each query individually

3. For scientific topics:
   ~~academic_search(query) — add academic results

4. For facts:
   ~~search(query) — AI-synthesized answers

5. On error from any provider → try next in chain (see CONNECTORS.md)

Tool selection by type:

Type	Primary	Additional
Competitive Analysis	~~search	~~extract for pricing
Market Research	~~search	~~search (different provider for details)
Technical Audit	~~code_search	~~search for docs
Person/Company Lookup	Exhaustive Discovery Protocol	~~search for facts
Topic Deep Dive	~~batch_search	~~academic_search for papers
News & Trends	~~search	~~search (with date filter)

Step 4: READ

Read top-5 pages using ~~scrape / ~~batch_scrape with fallback.

1. Collect all URLs from search results
2. Rank by relevance → top results
3. Select top-5 (or top-N based on depth)
4. ~~batch_scrape(top_urls) → get content
   Fallback: ~~scrape per URL individually

Priority:
- Official sites > reputable sources > blogs
- Recent > older (check publication date)
- Primary sources > secondary

Step 5: EXTRACT

Extract key data from the content read.

From each page extract:
- Key facts and claims
- Numbers, metrics, data points
- Direct quotes (with attribution)
- Dates and timeline events

Tools:
- Text classification → categorize content
- ~~extract(urls, schema) → structured data
- For PDFs: PDF extraction → full text

Step 6: SYNTHESIZE

Combine data, deduplicate, cross-check.

1. Deduplicate → remove redundant info
2. Cross-check: compare facts from different sources
   - Same fact from 3+ sources → High confidence
   - Same fact from 2 sources → Medium confidence
   - Single source only → Low confidence (flag it)
3. Identify contradictions → note in Gaps section
4. Identify information gaps → note what was NOT found

Step 7: REPORT

Generate a structured report.

1. Select template based on research_type
   (see report-generation skill for full templates)

2. Fill in all sections:
   - Key Findings with inline citations
   - Data tables with sources
   - Quotes with attribution
   - Gaps & Limitations

3. ALWAYS include Methodology:
   - Research type
   - Providers used (which responded, which failed)
   - Search queries (full list)
   - Pages analyzed (count)
   - Date of research
   - Limitations

4. Output the report in markdown

Quality Checklist

Before delivering any report, verify:

• Research type correctly classified
• Minimum 3 search queries from different angles
• At least 3-5 pages read and analyzed
• Every fact has a URL source
• Data cross-checked across sources
• Confidence levels assigned (High/Medium/Low)
• Gaps and limitations documented
• Methodology section complete
• Date of research included
• Report uses correct template for research type