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Market Research Reports

Builds auditable market research reports where every claim maps to a source and TAM/SAM/SOM plus forecasts are presented as scenarios.

Data & AnalyticsIntermediate★ 33,030⑂ 3,248AI score 8/10Last updated: Aug 9, 2026

What it does

  • Locks the market definition first — product, customer, geography, channel, period, measure, unit, denominator, currency/base year, and taxonomy — so the numbers stay comparable.
  • Maintains a source ledger and a claims ledger with stable IDs (S-001, C-001) and ships validation CLIs that catch broken claim-to-source mappings.
  • Sizes the market top-down and bottom-up independently, enforces disjoint coverage keys, reconciles the gap, and reports at least two genuinely different scenarios.
  • Treats forecasts as conditional scenarios, not probabilities, with sensitivity, switching values, and invalidation conditions.
  • Includes competitor matrix validation, unit-consistency checks, and Markdown/LaTeX report scaffold generators. All bundled scripts are standard-library and local-only (no network, LLM, or pickle calls).

Explicit prohibitions: no brand impersonation, no invented citations or market shares, no investment/legal advice, no PII in artifacts.

Who it's for

  • Strategy and corp-dev teams who need traceable market sizing for board or investment memos.
  • Founders who want defensible TAM numbers in a fundraising deck.
  • Research and consulting teams producing recurring industry reports with a consistent methodology.
  • Analysts working with official statistics and filings who must document source lineage.

Examples

  1. B2B SaaS market sizing — "Estimate TAM for mid-market HR SaaS top-down and bottom-up and explain the gap" → denominator definition, customer count × addressable fraction × price, and a documented reconciliation.
  2. Three-year demand outlook — run forecast_sensitivity.py to produce downside/base/upside ranges by year, the most influential assumptions, and switching values.
  3. Competitive landscape — build a feature matrix pinned to one product edition, geography, and as-of date, marking missing public evidence as unknown rather than no, then validate it with the bundled script.

· · · Install guide · · ·

Install in the Claude app (no terminal)
  1. Download the ZIP with the button below.
  2. In Claude, open Settings → Capabilities and turn on 'Code execution and file creation'. (one time)
  3. Go to Customize → Skills → + → 'Upload a skill' and upload the ZIP.
↓ Download ZIP
Install in Claude Code

Let Claude do it — paste this into Claude Code

Install the skill I found on Claude Skill Mart.
Copy the skills/market-research-reports folder from the GitHub repo K-Dense-AI/scientific-agent-skills into my ~/.claude/skills/market-research-reports/.
When it's done, tell me in one line what this skill can do.

Install with a command instead

git clone https://github.com/K-Dense-AI/scientific-agent-skills.git && mkdir -p ~/.claude/skills && cp -r scientific-agent-skills/skills/market-research-reports ~/.claude/skills/

⚠ This is a third-party skill. Check the source repository before installing.

  1. Open a terminal (Terminal on macOS, WSL or Git Bash on Windows).
  2. Confirm Python 3.11+ is available: python3 --version.
  3. Clone the repository: 
    git clone https://github.com/K-Dense-AI/scientific-agent-skills.git
  4. Copy the skill folder — keep scripts/, references/, and assets/ together: 
    mkdir -p ~/.claude/skills
cp -r scientific-agent-skills/skills/market-research-reports ~/.claude/skills/
  5. Restart Claude Code and verify market-research-reports appears in your skill list.
  6. Trigger it with a request like "size this market with TAM/SAM/SOM scenarios and a source ledger."
  7. Optional: install XeLaTeX or LuaLaTeX if you want to use the bundled LaTeX report template.
View source on GitHub ↗License: MIT