market-research-reports
Build evidence-traceable market research reports and assumption-driven market sizing or forecast scenarios. Use for market definition, industry and customer evidence, competitive landscapes, TAM/SAM/SOM reconciliation, forecast sensitivity, and auditable report scaffolds.
npx skills add K-Dense-AI/claude-scientific-writer --skill market-research-reports --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Market Research Reports ## Purpose Create decision-focused market reports whose claims, calculations, assumptions, and uncertainties can be audited. Match depth and format to the question and evidence. There is no required length, chapter count, visual count, or output format. Do not: - imitate or imply affiliation with a consulting, analyst, or research brand; - invent citations, quotes, market shares, or paid-market figures; - present TAM/SAM/SOM or a forecast as one certain truth; - treat a framework, chart, or fluent narrative as evidence; - provide investment, legal, antitrust, tax, accounting, or regulatory advice. ## Operating principles 1. **Define before sizing.** Fix product, customer, geography, channel, period, measure, unit, denominator, currency/base year, and taxonomy. 2. **Map every claim.** Every factual or quantitative claim has a claim ID and exact source IDs. 3. **Separate statement types.** Distinguish facts, estimates, calculations, forecasts, opinions, and recommendations. 4. **Prefer primary evidence.** Use official statistics, regulator records, filed company disclosures, and transparent original studies before secondary synthesis. 5. **Preserve uncertain
- Purpose
- Operating principles
- Workflow
- 1. Establish the research contract
- 2. Build the evidence plan
- 3. Create the source ledger
- 4. Maintain a claims ledger
- 5. Size the market as scenarios
- 6. Forecast with explicit uncertainty
- 7. Analyze customers and primary research
- 8. Analyze competitors and concentration
- 9. Normalize units and definitions
- 10. Draft and review
- Release gate
python3 scripts/validate_evidence_ledger.py data/source_ledger.csv python3 scripts/audit_claim_citations.py \ data/claims.csv data/source_ledger.csv python3 scripts/calculate_market_sizing.py \ assets/market_sizing_scenarios_template.json python3 scripts/forecast_sensitivity.py \ assets/forecast_sensitivity_template.json python3 scripts/validate_competitor_matrix.py \ assets/competitor_feature_matrix_template.csv \ python3 scripts/check_unit_consistency.py \
What does the market-research-reports skill do?
Build evidence-traceable market research reports and assumption-driven market sizing or forecast scenarios. Use for market definition, industry and customer evidence, competitive landscapes, TAM/SAM/SOM reconciliation, forecast sensitivity, and auditable report scaffolds.
How do I install it?
Run `npx skills add K-Dense-AI/claude-scientific-writer --skill market-research-reports --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From K-Dense-AI/claude-scientific-writer, a repository with 2,169 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.