Agent Skills
› NeverSight/learn-skills.dev
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market-research
GitHub提供市场研究、竞品分析、投资尽职调查及行业情报，支持TAM估算与决策。强调来源引用、数据时效性、反面证据及明确建议，输出结构化报告以辅助商业决策。
Trigger Scenarios
市场调研或技术趋势分析
构建TAM/SAM/SOM估算
竞品对比或产品分析
投资者背景调查
验证商业假设
Install
npx skills add NeverSight/learn-skills.dev --skill market-research -g -y
SKILL.md
Frontmatter
{
"name": "market-research",
"origin": "ECC",
"description": "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."
}
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
Version History
- e0220ca Current 2026-07-05 23:45
