market-research

Conduct market research, competitive analysis, investor due diligence, and industry intelligence with source attribution and decision-oriented summaries. Use when the user wants market sizing, competitor comparisons, fund research, technology scans, or research that informs business decisions.

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Install skill "market-research" with this command: npx skills add affaan-m/everything-claude-code/affaan-m-everything-claude-code-market-research

Market Research

Produce research that supports decisions, not research theater.

When to Activate

  • researching a market, category, company, investor, or technology trend
  • building TAM/SAM/SOM estimates
  • comparing competitors or adjacent products
  • preparing investor dossiers before outreach
  • pressure-testing a thesis before building, funding, or entering a market

Research Standards

  1. Every important claim needs a source.
  2. Prefer recent data and call out stale data.
  3. Include contrarian evidence and downside cases.
  4. Translate findings into a decision, not just a summary.
  5. Separate fact, inference, and recommendation clearly.

Common Research Modes

Investor / Fund Diligence

Collect:

  • fund size, stage, and typical check size
  • relevant portfolio companies
  • public thesis and recent activity
  • reasons the fund is or is not a fit
  • any obvious red flags or mismatches

Competitive Analysis

Collect:

  • product reality, not marketing copy
  • funding and investor history if public
  • traction metrics if public
  • distribution and pricing clues
  • strengths, weaknesses, and positioning gaps

Market Sizing

Use:

  • top-down estimates from reports or public datasets
  • bottom-up sanity checks from realistic customer acquisition assumptions
  • explicit assumptions for every leap in logic

Technology / Vendor Research

Collect:

  • how it works
  • trade-offs and adoption signals
  • integration complexity
  • lock-in, security, compliance, and operational risk

Output Format

Default structure:

  1. executive summary
  2. key findings
  3. implications
  4. risks and caveats
  5. recommendation
  6. sources

Quality Gate

Before delivering:

  • all numbers are sourced or labeled as estimates
  • old data is flagged
  • the recommendation follows from the evidence
  • risks and counterarguments are included
  • the output makes a decision easier

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

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