agents-store 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