market-research▌
affaan-m/everything-claude-code · updated Apr 8, 2026
Research-backed market intelligence with source attribution and decision-oriented analysis.
- ›Covers investor diligence, competitive analysis, market sizing, and technology vendor research with structured output including findings, implications, risks, and recommendations
- ›Enforces sourcing standards: every claim requires attribution, stale data is flagged, and contrarian evidence is included alongside supporting data
- ›Separates fact, inference, and recommendation clearly to support deci
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
- Every important claim needs a source.
- Prefer recent data and call out stale data.
- Include contrarian evidence and downside cases.
- Translate findings into a decision, not just a summary.
- 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:
- executive summary
- key findings
- implications
- risks and caveats
- recommendation
- 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
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★30 reviews- ★★★★★Layla Verma· Dec 20, 2024
We added market-research from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Aisha Agarwal· Dec 12, 2024
Keeps context tight: market-research is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Shikha Mishra· Dec 8, 2024
market-research is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Amelia Abbas· Dec 8, 2024
Useful defaults in market-research — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Yash Thakker· Nov 27, 2024
Useful defaults in market-research — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Daniel Chawla· Nov 27, 2024
market-research is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Dhruvi Jain· Oct 18, 2024
Registry listing for market-research matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Amelia Ramirez· Oct 18, 2024
market-research reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Zaid Gupta· Sep 13, 2024
market-research fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Fatima Sanchez· Aug 4, 2024
market-research has been reliable in day-to-day use. Documentation quality is above average for community skills.
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