Systematic validation for testing ideas before building: define hypotheses, collect evidence, score the opportunity, and make a decision you can defend.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionstartup-idea-validationExecute the skills CLI command in your project's root directory to begin installation:
Fetches startup-idea-validation from vasilyu1983/ai-agents-public 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-idea-validation. Access via /startup-idea-validation 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.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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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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Systematic validation for testing ideas before building: define hypotheses, collect evidence, score the opportunity, and make a decision you can defend.
GO / CONDITIONAL / PIVOT / NO-GO and a next action.| If the user asks… | Produce… | Use… |
|---|---|---|
| “Validate this idea” / “Is this worth building?” | 9-dimension scorecard + verdict | validation-scorecard.md, go-no-go-decision.md |
| “What’s the riskiest assumption?” | RAT + test plan | riskiest-assumption-test.md, validation-experiment-planner.md |
| “Test my hypothesis” | Hypothesis canvas + experiment design | hypothesis-canvas.md, hypothesis-testing-guide.md |
| “Market size for X” | TAM/SAM/SOM sizing + assumptions table | market-sizing-worksheet.md, market-sizing-patterns.md |
| “Can this be profitable / what’s my runway?” | Unit economics + runway + scenarios | financial-modeling-calculator.md |
| “Should I build X or Y?” | Comparative scorecard + decision memo | validation-scorecard.md, go-no-go-decision.md |
| Dimension | Weight | What it measures |
|---|---|---|
| Problem severity | 15% | Urgency, cost of inaction, current workarounds |
| Market size | 12% | Sufficient demand for the target outcome |
| Market timing | 10% | Clear “why now” and tailwinds |
| Competitive moat | 12% | Defensibility over time |
| Unit economics | 15% | Profit path (incl. payback and margins) |
| Founder-market fit | 8% | Access, expertise, and execution capability |
| Technical feasibility | 10% | Buildability, dependencies, constraints |
| GTM clarity | 10% | ICP, channels, motion, first customers |
| Risk profile | 8% | What can kill it and likelihood |
Verdict thresholds (default):
80–100: GO60–79: CONDITIONAL (validate RAT first)40–59: PIVOT<40: NO-GODeep scoring rubrics and calibration live in validation-methodology.md.
| Step | Goal | Strong signal |
|---|---|---|
| Interviews | Validate the problem and context | Repeated pain with real workarounds and spend |
| Smoke test | Validate demand | Qualified conversion with price shown |
| Concierge/WoZ | Validate workflow value | Users complete the job and return |
| Paid pilot | Validate willingness-to-pay | Paid, renewed, or expanded |
If the idea depends on AI (agents, copilots, automation), validate these explicitly:
assets/financial-modeling-calculator.md.See hypothesis-testing-guide.md for AI-specific experiment patterns.
| Resource | Purpose |
|---|---|
| validation-methodology.md | Scoring rubrics and calibration |
| hypothesis-testing-guide.md | Experiment design and RAT workflows |
| market-sizing-patterns.md | TAM/SAM/SOM methods and pitfalls |
| moat-assessment-framework.md | Defensibility analysis |
| customer-interview-guide.md | Interview methodology, scripts, and analysis |
| landing-page-validation.md | Smoke tests, conversion benchmarks, landing page tools |
| competitive-landscape-assessment.md | Competitive scan, gap analysis, market mapping |
| pivot-framework.md | Pivot triggers, types, decision framework, case studies (Slack, Instagram, Shopify) |
| Template | Purpose |
|---|---|
| validation-scorecard.md | Full 9-dimension scoring |
| go-no-go-decision.md | Decision memo format |
| hypothesis-canvas.md | Hypothesis definition |
| validation-experiment-planner.md | Experiment planning + thresholds |
| riskiest-assumption-test.md | RAT identification and test design |
| market-sizing-worksheet.md | Sizing worksheet |
| financial-modeling-calculator.md | Runway + scenarios + unit economics |
| File | Purpose |
|---|---|
| sources.json | Curated validation resources |
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.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
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mattpocock/skills
startup-idea-validation is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Registry listing for startup-idea-validation matched our evaluation — installs cleanly and behaves as described in the markdown.
startup-idea-validation fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
startup-idea-validation has been reliable in day-to-day use. Documentation quality is above average for community skills.
Registry listing for startup-idea-validation matched our evaluation — installs cleanly and behaves as described in the markdown.
Solid pick for teams standardizing on skills: startup-idea-validation is focused, and the summary matches what you get after install.
startup-idea-validation reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added startup-idea-validation from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
startup-idea-validation reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend startup-idea-validation for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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