startup-validator by ailabs-393/ai-labs-claude-skills
npx skills add https://github.com/ailabs-393/ai-labs-claude-skills --skill startup-validator一个通过系统性市场研究、竞争分析、问题验证和定位策略来分析创业想法的综合工具。此技能帮助评估一个创业想法是否具有真正的市场潜力以及如何有效地进行定位。
当用户提出一个创业想法时,请遵循此系统性验证流程:
在开始研究前确保完全理解:
提取关键信息:
仅在关键信息缺失时提出澄清性问题:
不要询问您可以独立研究的信息(市场规模、竞争对手、趋势)。
基于该想法,创建一个研究计划,确定:
使用 references/research_templates.md 中的模板来制定查询。
在所有维度上执行系统性研究。始终使用至少 10-15 次网络搜索以确保分析透彻。
搜索:
广告位招租
在这里展示您的产品或服务
触达数万 AI 开发者,精准高效
查询示例:
搜索:
查询示例:
搜索:
查询示例:
搜索:
查询示例:
搜索:
查询示例:
关键: 使用 web_fetch 阅读来自权威来源(Gartner、McKinsey、Statista、Crunchbase、行业报告)的完整文章,以获取详细数据,而不仅仅是片段。
收集数据后,使用 references/frameworks.md 中的框架进行分析:
可选: 如果有定量数据可用,创建一个 JSON 文件并使用 scripts/market_analyzer.py 来计算指标并生成额外的见解。
清晰阐述:
制定具体建议:
创建一个全面的 Markdown 报告,包含:
# [创业想法] 验证报告
## 执行摘要
- 一段式概述
- 最终建议:强烈推荐推进 / 建议进行验证 / 建议调整方向 / 不可行
- 3-5 个关键发现
## 市场分析
### 市场规模与增长
- 带来源的 TAM/SAM/SOM 估计
- 增长率和轨迹
- 市场成熟度评估
### 市场趋势
- 关键有利趋势
- 潜在阻力
- 时机考虑
## 竞争格局
### 直接竞争对手
- 列表及简要描述
- 市场份额/地位
- 优势和劣势
### 间接竞争
- 替代解决方案
- 替代品
### 竞争空白
- 未满足的需求
- 定位机会
## 问题-解决方案契合度
### 问题验证
- 问题存在的证据
- 频率和强度
- 当前解决方案及局限性
### 解决方案差异化
- 独特的价值主张
- 竞争优势
- 潜在护城河
## 商业模式评估
### 收入模式
- 定价策略匹配度
- 单位经济效益潜力
- 可扩展性因素
### 客户获取
- 主要渠道
- CAC 考虑因素
- 销售周期估计
## 风险分析
### 关键风险
- 交易破坏者
- 主要挑战
### 可管理风险
- 可解决的问题
- 缓解策略
## 定位建议
### 目标市场
- 主要客户细分
- 滩头市场策略
### 价值主张
- 核心利益陈述
- 关键差异化因素
### 市场进入策略
- 分销方法
- 合作机会
- 初始吸引力策略
## 验证后续步骤
1. 验证假设的立即行动
2. 所需的客户访谈
3. 需要测试的 MVP 或原型
4. 需要跟踪的指标
## 来源
[列出所有关键来源及链接]
格式指南:
references/frameworks.md 中的多个框架references/frameworks.md全面的市场分析框架,包括:
使用时机: 在整个分析过程中参考,以确保对所有维度进行全面评估。
references/research_templates.md搜索查询模板和可靠数据来源,包括:
使用时机: 在研究计划和执行期间,用于制定有效的搜索并识别权威来源。
scripts/market_analyzer.py用于定量市场分析的 Python 脚本:
使用时机: 当有定量数据可用且计算能加强分析时。通过 JSON 文件输入数据,输出计算出的指标和 Markdown 报告部分。
使用示例:
python scripts/market_analyzer.py analysis_data.json
输入格式:
{
"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
}
}
用户可能使用以下短语请求验证:
每周安装次数
129
代码仓库
GitHub 星标数
322
首次出现
2026年1月23日
安全审计
安装于
opencode110
codex103
gemini-cli101
claude-code98
cursor93
github-copilot88
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:
Weekly Installs
129
Repository
GitHub Stars
322
First Seen
Jan 23, 2026
Security Audits
Gen Agent Trust HubPassSocketPassSnykWarn
Installed on
opencode110
codex103
gemini-cli101
claude-code98
cursor93
github-copilot88
创业转型指南:如何利用四P框架决定何时进行200%的转型
795 周安装