Agent skill · research science · affaan-m
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.
Why this skill is useful
Provides structured methodologies and standards for conducting market research that the AI wouldn't reliably generate on its own.
What it needs
About 1k tokens when loaded. Last updated 2026-08-06. 238,342 stars on the source repository.
What this skill does
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
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills affaan-m/market-research--119cd4