Deep research
Use when the user asks to 'research trends', 'analyze a topic', 'fact-check this', 'verify claims', 'what's the state of X', or hands you a document to vet. A disk-first, checkpointed research workflow with three modes — trend research, topic analysis, and fact-checking.From its SKILL.md
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SKILL.md
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Deep Research
One workflow, three modes. Pick the mode from the user's intent:
| Mode | Use when |
|---|---|
| trends | "what's happening in X", "emerging patterns", "who are the players" |
| analyze | "go deep on X", "tradeoffs of X", "SWOT", "compare perspectives" |
| factcheck | document or list of claims handed in for verification |
All three share the same workspace + checkpoint discipline below. Read this section once, then jump to your mode.
Workspace & Checkpointing (all modes)
Workspace: .research/<YYYY-MM-DD>/<mode>_<session>/
00_plan.md # written before any research
notes.md # rolling findings, source URLs
checkpoint_NNN.md # batch results (factcheck) or section drafts (trends/analyze)
report.md # final output, assembled from disk — never from memory
Rules that apply to every mode:
- Plan first. Write
00_plan.mdbefore searching anything. Include the question, sub-questions, and the sources you intend to hit. - Disk is truth, memory is scratch. Append findings to
notes.mdas you go with source URLs. If the session dies, you resume from disk. - Checkpoint on a budget. Every ~10 research steps OR when context approaches ~150K tokens, write a checkpoint and drop detailed research from working memory — keep only 2–3 line summaries.
- Assemble the final report from disk. Use
cat/Readover checkpoints. Never reconstruct from memory. - Resume, don't restart. On error,
lsthe workspace, read the last checkpoint, continue from the next unprocessed item.
Mode: trends
Goal: identify the current state and trajectory of a space.
- Plan sub-questions: who are the players, what's new in the last 6–12 months, what are adoption signals, what are the contrarian takes.
tavily_searchfor each sub-question. For technical topics, alsoresolve-library-id+query-docs(Context7) to ground claims in current docs.- Note publication dates aggressively — anything older than 12 months gets flagged as "background, not signal."
- Final
report.md:- State of the space (2–3 paragraphs)
- Key players (table: name, focus, signal)
- Emerging patterns (bullets, each with a dated source)
- Contrarian / risk signals
- Where this is heading (1 paragraph, clearly labeled as opinion)
Prioritize actionable insight over exhaustive coverage.
Mode: analyze
Goal: deep, balanced decomposition of a single topic.
- Plan: break the topic into core components, stakeholder perspectives, and decision axes.
- Research each component with
tavily_search/tavily_extract. For each, capture both the strongest case for and the strongest case against. - Final
report.md:- Executive summary (3–5 sentences, no hedging)
- Components (one section each)
- Perspectives & counterarguments
- SWOT (or equivalent: tradeoffs, risks, opportunities)
- Recommendation with reasoning, clearly separated from facts
Depth over breadth. Nuance over coverage.
Mode: factcheck
Goal: extract every factual claim from a document and label each one with evidence.
Setup
Readthe document.- Extract every factual claim (statements presented as objective truth — stats, dates, quotes, attributions, causal claims). Write all of them, numbered, to
00_claims_extracted.mdbefore any verification. - Skip opinions, predictions, value judgments. Mark them in a separate
opinions.mdif useful for the final summary. - Categorize: statistical / historical / scientific / attributional. Order by significance.
Verification (batches of 8–10)
For each batch:
tavily_searchfor current/breaking and synthesis-heavy claims,tavily_extractfor primary-source verification.- Aim for ≥2 independent sources per claim. Note publication dates and source authority.
- Watch for context manipulation (accurate quote, misleading framing) and outdated facts presented as current.
- Write
checkpoint_NNN.mdwith full findings for the batch, then drop the details from memory — keep onlyclaim# | verdict | confidencelines.
Checkpoint format:
# Checkpoint NNN — Claims X–Y
## Claim #X: <verbatim claim>
**Status**: VERIFIED | FALSE | MISLEADING | UNVERIFIABLE | OUTDATED
**Evidence**: <urls>
**Analysis**: <what the sources say vs. the claim>
**Confidence**: HIGH | MEDIUM | LOW
Final report
Read all checkpoints from disk and assemble report.md:
## FACT-CHECK REPORT: <doc title>
### Summary
<N claims checked: V verified, F false, M misleading, U unverifiable, O outdated>
### Detailed Findings
<one block per claim, same format as checkpoint>
### Overall Assessment
<one paragraph on the document's factual reliability>
Be impartial. Distinguish FALSE (contradicted by evidence) from UNVERIFIABLE (insufficient evidence either way). Cite sources for every verdict.
Cross-mode rules
- Never fabricate sources. If you can't find evidence, say so.
- Never include raw page dumps in the final report — summarize and link.
- Flag conflicting evidence rather than picking a winner silently.
- Mask any PII / credentials encountered during searches.