deep-research

Deep Research

Better than plain websearch. Faster than full research pipelines.

What makes it better:

1. Landscape Scan — discovers what exists before searching specifics (avoids blind spots)
2. Recency Pulse — catches releases from last 7-30 days, searches upstream providers
3. Parallel search — 2-3 queries at once, multiple angles simultaneously

For rigorous research (hypotheses, COMPASS audit, Red Team, full report) → /deep-research-pro

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Step 1: CLASSIFY

Type	When	Do
A	Single fact	Search → answer directly
B	Multi-fact / comparison	SCAN → RECENCY → SEARCH → Synthesize
C	Judgment / recommendation	B + flag uncertainty + note limitations

Tiers: Quick (5-10 sources) · Standard (10-20 sources)

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Step 2: LANDSCAPE SCAN (skip for Type A)

Map what exists before searching specifics. Never use known names in scan queries — you'll miss things that exist but you don't know about yet.

❌ "DeepSeek Qwen performance 2026"   ← only finds what you already know
✅ "China open source LLM list 2026"  ← discovers the full landscape

Queries (parallel):

WebSearch: "[topic] landscape overview [current year]"
WebSearch: "top [topic] list [current year]"
WebSearch: "[topic] all options [current year]"

Extract entity names → split into Discovered (new) vs Confirmed (updated).

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Step 3: RECENCY PULSE (mandatory for tech/AI topics)

Yearly searches miss releases from last week. Downstream product news lags upstream by weeks.

Map supply chain first: Who makes the underlying tech? → Search them directly.

WebSearch: "[topic] latest news [current month] [current year]"
WebSearch: "[upstream provider] latest release [current month] [current year]"

Example — researching "Microsoft Copilot": Upstream = OpenAI + Anthropic → search both directly, don't rely on Microsoft announcements alone.

Flag anything from last 7-30 days as RECENT or BREAKING.

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Step 4: SEARCH

Run queries in parallel (single message, multiple tool calls):

WebSearch: "[topic] [current year]"
WebSearch: "[topic] limitations problems"
WebSearch: "[topic] vs alternatives comparison"

Stop when: 3 consecutive searches add <10% new info (saturation) or sources converge on same answer.

URL fallback (403/blocked):

curl -s --max-time 60 "https://r.jina.ai/https://example.com"

Claim confidence:

• C1 (key claims) — need 2+ sources + confidence note: HIGH / MEDIUM / LOW
• C2 (supporting) — citation required
• C3 (common knowledge) — cite only if contested

Never state C1 without citing [N]. If no source found → say so.

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Step 5: SYNTHESIZE + SAVE

For each key finding, answer:

• แล้วยังไง (So what)? — why does this matter?
• ต้องทำอะไร (Now what)? — action to take?

If sources conflict: flag explicitly — "Source A says X, Source B says Y — likely because [reason]."

Always save output:

research/[topic-slug]-[YYYY-MM-DD].md

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When to Ask vs Just Do

Ask	Just do
Topic too broad → "อยากเน้นมุมไหนคะ?"	Choose search queries
Interesting sub-topic found	Format output
Sources conflict on key point	Type A questions

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Related Skills

• /deep-research-pro — Full pipeline: hypotheses, QUEST queries, COMPASS audit, Red Team, formal report
• /boost-intel — Stress-test a research finding before making a decision
• /generate-creative-ideas — Cross-industry creative research (no web search needed)