aaaaqwq/agi-super-team/market-research

Claude Code and agent skill by aaaaqwq/agi-super-team

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Size markets, analyze competitors, and validate opportunities with practical frameworks and free data sources.

Install

npx vskill@latest install aaaaqwq/agi-super-team/market-research

SKILL.md

Core Framework

Before any research: Clarify the question. "How big is the market?" is useless. "How many [target customers] in [geography] would pay [price] for [solution] annually?" is actionable.

Market Sizing

MethodUse WhenApproach
Bottom-upYou have unit economicsCustomers × Price × Frequency
Top-downExploring new marketsTAM → SAM → SOM with clear filters
ComparableSimilar products existCompetitor revenue × market share estimate

Free data sources: Government census, industry associations, public company filings (10-K), Statista free tier, Google Trends, LinkedIn Sales Navigator (company counts).

Red flag: If your SAM equals your TAM, you haven't thought hard enough about who actually buys.

Competitor Analysis

  1. Map the landscape: Direct, indirect, potential entrants
  2. Mine reviews: G2, Capterra, App Store — recurring complaints = opportunities
  3. Track signals: Job postings (what they're building), pricing changes, feature launches
  4. Assess moats: Network effects, switching costs, data advantages, regulatory capture

For detailed competitor frameworks, see competitor-analysis.md.

Customer Validation

Before building: Talk to 20+ potential customers. Use Jobs-to-be-Done or Mom Test frameworks.

Signals that matter: LOIs, prepayments, waitlist-to-signup conversion, repeat usage Signals that don't: "I'd use that," survey enthusiasm, social media likes

For interview scripts and survey templates, see validation.md.

Common Traps

  • Confirmation bias: Seeking data that supports your thesis
  • Survivorship bias: Only studying successful companies
  • Outdated sources: Tech markets shift in months, not years
  • Vanity metrics: Downloads, followers, page views without retention/revenue

Boundaries

  • No financial advice: Cannot recommend investments based on market research
  • No guarantees: All market forecasts are probabilistic
  • Escalate to professionals: For statistically valid primary research, regulated industries, or deep competitive intelligence

Security

  • Security scanPassed, 95 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
98
Repository forks
23
7-day trend score
23

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 21 Sep 2026, a month ago.

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