desk-research

# Desk Research Execute this workflow for any desk-research request. ## 0) Load methodology checklist (first) Read `references/methodology.md`, `references/deep-writing-patterns.md`, and `references/quality-checklist.md` and apply all as guardrails. ## 1) Define the research brief Write 4 lines before searching: - Research question (1 sentence) - Scope (time, geography, industry) - Must-answer sub-questions (3-6 bullets) - Output format needed by user If the question is vague, propose assumptions explicitly and continue. ## 2) Build a source plan Collect evidence in this priority order: 1. Primary/official sources (government, regulator, company filings, product docs) 2. Reputable secondary analysis (major research firms, established media) 3. Community signals (forums/social) only as supporting evidence Require at least 2 independent sources for every key claim. ## 3) Gather evidence fast For each sub-question: - Find 3-8 candidate sources - Keep the highest-signal sources - Extract only claim + evidence + date + link Reject sources that are undated, anonymous, or purely opinionated unless the user asked for sentiment. ## 4) Score source reliability Tag each source: - A = official primary source - B = credible secondary source - C = weak/indicative source When claims conflict, prefer newer A/B sources and explicitly note uncertainty. ## 5) Synthesize insights Convert notes into: - Facts (well-supported) - Interpretations (reasoned but inferential) - Unknowns (gaps needing validation) Never present interpretation as fact. ### Source hard rule (critical) For all final research outputs: - Every major factual claim must include source + date. - Every key viewpoint, analytical framework, stage model, or category split must either: 1. cite a source, or 2. be explicitly labeled as the report author's synthesis / working model. - Do not present an unsupported framework as if it were an established industry fact. - If a conclusion combines multiple sources, cite the main supporting sources inline or in the same paragraph. ## 5.5) Deepening loop (mandatory) Before final delivery, run at least 2 rounds of self-questioning: Round A — Coverage challenge - What did I miss by source type, time window, or geography? - Which category/conclusion is over-dependent on one source? - What contradicts my current conclusion? Round B — Decision challenge - If this conclusion is wrong, what evidence would prove it wrong? - Which part is descriptive but not decision-useful? - What next data pull would most change the recommendation? After each round, update findings and confidence. ## 6) Deliver in concise structure Use this exact section order: 1. Core Questions (2 questions) 2. One-sentence Verdict 3. Executive Summary (5-8 bullets) 4. Key Findings by sub-question (with metric anchors) 5. Evidence Table (claim | source | date | reliability) 6. Confidence tags (High/Medium/Low per major claim) 7. Risks / Uncertainty 8. What would falsify this conclusion 9. Next Verification Steps / Todo Inline citation rule: - In the body, append source/date after key claims whenever it helps verification. - For analytical frameworks or stage models, add `Source:` or `Author synthesis based on:` explicitly. - Do not leave major frameworks floating without attribution. For output shape and compact template, use `references/output-template.md`. ## 7) Quality bar before sending Check all items: - Every major claim has source/date - No single-source critical claim - Time/geography scope matches user ask - Clear separation of fact vs interpretation - Actionable takeaway included - Each promising case uses the full 9-part deep case framework - Each promising case includes one final case-summary paragraph: what it does / who pays / business model / why pay - Each key section ends with decision implication (so-what) ## 8) Case-depth hard rule (for startup/case research) When the task is startup/use-case research, apply these hard requirements: - For each promising case, collect at least 3 website evidence snippets (feature/pricing/use-flow) - Add at least 1 metric anchor from trusted dataset (revenue/MRR/growth) - Include at least 1 risk point and 1 falsification condition - Do not submit if any case is only descriptive without judgment