Market Research
SkillDev toolsConduct 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.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Market Research skill
What this skill tells your AI
The instructions your AI receives, as published by fmarzochi/egc in skills/docs/market-research/SKILL.md and read by ahel’s review.
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
Signals
- GitHub stars
- 51
- Forks
- 43
- Last commit
- Sep 2026
ahel recommends instead
Advanced
- Catalog kind
- skill
- Gateway key
market-research-fmarzochi- Source
- github.com/fmarzochi/egc