A comprehensive tool for analyzing startup ideas through systematic market research, competitive analysis, problem validation, and positioning strategy. This skill helps evaluate whether a startup idea has genuine market potential and how to position it effectively.
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionstartup-validatorExecute the skills CLI command in your project's root directory to begin installation:
Fetches startup-validator from ailabs-393/ai-labs-claude-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate startup-validator. Access via /startup-validator in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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A comprehensive tool for analyzing startup ideas through systematic market research, competitive analysis, problem validation, and positioning strategy. This skill helps evaluate whether a startup idea has genuine market potential and how to position it effectively.
When a user presents a startup idea, follow this systematic validation process:
Ensure complete understanding before research begins:
Extract key information:
Ask clarifying questions only if critical information is missing:
Do not ask for information you can research independently (market size, competitors, trends).
Based on the idea, create a research plan identifying:
Use templates from references/research_templates.md for query formulation.
Execute systematic research across all dimensions. Always use at least 10-15 web searches to ensure thorough analysis.
Search for:
Query examples:
Search for:
Query examples:
Search for:
Query examples:
Search for:
Query examples:
Search for:
Query examples:
CRITICAL: Use web_fetch to read full articles from authoritative sources (Gartner, McKinsey, Statista, Crunchbase, industry reports) to get detailed data, not just snippets.
After gathering data, analyze using frameworks from references/frameworks.md:
Optional: If quantitative data is available, create a JSON file and use scripts/market_analyzer.py to calculate metrics and generate additional insights.
Clearly articulate:
Develop specific recommendations:
Create a comprehensive markdown report with:
# [Startup Idea] Validation Report
## Executive Summary
- One-paragraph overview
- Bottom-line recommendation: STRONG GO / PROCEED WITH VALIDATION / PIVOT RECOMMENDED / NOT VIABLE
- 3-5 key findings
## Market Analysis
### Market Size & Growth
- TAM/SAM/SOM estimates with sources
- Growth rate and trajectory
- Market maturity assessment
### Market Trends
- Key favorable trends
- Potential headwinds
- Timing considerations
## Competitive Landscape
### Direct Competitors
- List with brief descriptions
- Market share/position
- Strengths and weaknesses
### Indirect Competition
- Alternative solutions
- Substitutes
### Competitive Gaps
- Unmet needs
- Positioning opportunities
## Problem-Solution Fit
### Problem Validation
- Evidence of problem
- Frequency and intensity
- Current solutions and limitations
### Solution Differentiation
- Unique value proposition
- Competitive advantages
- Potential moats
## Business Model Assessment
### Revenue Model
- Pricing strategy alignment
- Unit economics potential
- Scalability factors
### Customer Acquisition
- Primary channels
- CAC considerations
- Sales cycle estimates
## Risk Analysis
### Critical Risks
- Deal-breakers
- Major challenges
### Manageable Risks
- Addressable concerns
- Mitigation strategies
## Positioning Recommendations
### Target Market
- Primary customer segment
- Beachhead market strategy
### Value Proposition
- Core benefit statement
- Key differentiators
### Go-to-Market Strategy
- Distribution approach
- Partnership opportunities
- Initial traction strategy
## Validation Next Steps
1. Immediate actions to validate assumptions
2. Customer interviews needed
3. MVPs or prototypes to test
4. Metrics to track
## Sources
[List all key sources with links]
Formatting Guidelines:
references/frameworks.mdreferences/frameworks.mdComprehensive market analysis frameworks including:
When to use: Reference throughout analysis to ensure comprehensive evaluation across all dimensions.
references/research_templates.mdSearch query templates and reliable data sources including:
When to use: During research planning and execution to formulate effective searches and identify authoritative sources.
scripts/market_analyzer.pyPython script for quantitative market analysis:
When to use: When quantitative data is available and calculations would strengthen the analysis. Input data via JSON file, outputs calculated metrics and markdown report sections.
Example usage:
python scripts/market_analyzer.py analysis_data.json
Input format:
{
"startup_name": "Example Startup",
"market_data": {
"tam": 10000000000,
"sam": 2000000000,
"som": 200000000,
"current_market_size": 5000000000,
"growth_rate": 15,
"years": 5,
"competition_level": "medium",
"market_maturity": "growing"
},
"business_data": {
"cac": 500,
"ltv": 2000,
"monthly_revenue": 50,
"revenue": 1000,
"cost": 300
}
}
Insufficient research: Do not rely on 1-3 searches. Always conduct 10-15+ searches minimum.
Vague conclusions: Avoid statements like "the market is large" without specific numbers.
Missing critical dimensions: Ensure analysis covers market opportunity, competition, problem validation, trends, and business model.
Over-optimism: Present balanced view including real risks and challenges.
Poor source quality: Prioritize primary sources and reputable analysts over blog posts and promotional content.
Ignoring timing: Market readiness and trend timing are critical factors.
No actionable recommendations: Always provide specific next steps for validation.
Users may request validation using phrases like:
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
pproenca/dot-skills
startup-validator is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
startup-validator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
startup-validator has been reliable in day-to-day use. Documentation quality is above average for community skills.
startup-validator reduced setup friction for our internal harness; good balance of opinion and flexibility.
startup-validator is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Solid pick for teams standardizing on skills: startup-validator is focused, and the summary matches what you get after install.
Solid pick for teams standardizing on skills: startup-validator is focused, and the summary matches what you get after install.
Registry listing for startup-validator matched our evaluation — installs cleanly and behaves as described in the markdown.
Keeps context tight: startup-validator is the kind of skill you can hand to a new teammate without a long onboarding doc.
We added startup-validator from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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