AgentSkillsCN

startup-expertise

适用于构建初创公司功能、查阅行动指南、践行 YC 最佳实践,或需要行业专属指导时使用。可通过“初创公司”、“YC”、“行动指南”、“融资”、“路演”、“投资者”、“画布”、“验证”、“指标”等短语触发。

SKILL.md
--- frontmatter
name: startup-expertise
description: Use when building startup features, accessing playbooks, implementing YC best practices, or needing industry-specific guidance. Triggers on "startup", "YC", "playbook", "fundraising", "pitch", "investor", "canvas", "validation", "metrics".

Startup Expertise Skill

Purpose: Access YC-level startup knowledge, industry playbooks, and best practices for building StartupAI features.


When to Use This Skill

TriggerExample
Building startup features"Implement health score calculation"
Accessing playbooks"What metrics matter for SaaS?"
Industry guidance"Fashion startup best practices"
Fundraising features"Build investor matching"
Validation features"Implement canvas analysis"

1. Knowledge Sources

Industry Playbooks (19 Available)

Access via Supabase:

sql
-- Get playbook for specific industry
SELECT * FROM industry_playbooks WHERE industry_id = 'ai_saas';

-- List all available playbooks
SELECT industry_id, display_name FROM industry_playbooks WHERE is_active = true;
Industry IDDisplay NameKey Metrics
ai_saasAI SaaS / B2BMRR, CAC, LTV, churn, NRR
fintechFinTechTransaction volume, take rate, compliance
healthcareHealthcareOutcomes, regulatory, reimbursement
fashion_apparelFashion & ApparelSell-through, markdown %, inventory
ecommerce_pureeCommerceAOV, conversion, repeat purchase
educationEducationEnrollment, completion, outcomes
cybersecurityCybersecurityARR, net retention, certifications

Full list: Query SELECT industry_id, display_name FROM industry_playbooks

Playbook Fields Available

typescript
interface IndustryPlaybook {
  industry_id: string;
  display_name: string;
  narrative_arc: string;           // Story structure for pitches
  prompt_context: string;          // AI prompt enhancement
  investor_expectations: object;   // What investors look for
  failure_patterns: string[];      // Common mistakes
  success_stories: object[];       // Examples
  benchmarks: object;              // Industry benchmarks
  terminology: object;             // Industry-specific terms
  gtm_patterns: object;            // Go-to-market strategies
  decision_frameworks: object;     // How to make decisions
  investor_questions: string[];    // FAQ from investors
  warning_signs: string[];         // Red flags
  stage_checklists: object;        // Stage-specific tasks
  slide_emphasis: object;          // Pitch deck guidance
}

2. Prompt Packs

What Are Prompt Packs?

Pre-built AI workflows for common startup tasks. Each pack is a multi-step prompt sequence.

Available Categories

CategoryPacksUse Case
ValidationProblem validation, Customer interview, Market sizingEarly-stage founders
FundraisingPitch deck outline, Investor email, Due diligence prepRaising capital
GrowthChannel analysis, Retention strategy, Pricing modelScaling startups
PlanningOKR setting, Roadmap creation, Sprint planningExecution

Accessing Prompt Packs

typescript
// In edge function
const { data: pack } = await supabase
  .from('prompt_packs')
  .select('*')
  .eq('category', 'fundraising')
  .eq('name', 'pitch_deck_outline')
  .single();

// Execute pack steps
for (const step of pack.steps) {
  const result = await executePromptStep(step, context);
}

3. YC Best Practices

Why Startups Succeed (YC Data)

FactorWeightHow to Measure
Founder-Market Fit30%Domain expertise, passion, unfair advantage
Problem Clarity25%Can explain in one sentence, clear pain point
Traction Velocity20%Week-over-week growth rate
Market Size15%TAM/SAM/SOM with bottoms-up analysis
Team Completeness10%Technical + business + domain coverage

YC Application Tips

markdown
## What YC Partners Look For

1. **Clarity** - Can you explain your startup in one sentence?
2. **Traction** - What have you built? What do users say?
3. **Insight** - What do you know that others don't?
4. **Determination** - What obstacles have you overcome?
5. **Speed** - How fast do you move?

## Common Mistakes
- Vague problem description
- No customer quotes
- Feature-focused instead of problem-focused
- Unrealistic market size (top-down TAM)
- No unfair advantage articulated

Stage-Appropriate Guidance

StageFocusKey MetricsYC Advice
IdeaProblem validation# interviews, problem severity"Talk to users"
Pre-seedMVP + early usersActive users, engagement"Do things that don't scale"
SeedProduct-market fitRetention, NPS, growth rate"Make something people want"
Series ARepeatable growthUnit economics, CAC payback"Find your growth loop"

4. Implementing Startup Features

Health Score Calculation

typescript
// Reference: health-scorer edge function
interface HealthScore {
  overall: number;  // 0-100
  breakdown: {
    product: number;   // Feature completeness, user feedback
    market: number;    // Competition, timing, size
    team: number;      // Completeness, experience
    traction: number;  // Growth rate, engagement
    financial: number; // Runway, unit economics
  };
  recommendations: string[];
}

// Weights by stage
const stageWeights = {
  idea: { product: 0.3, market: 0.3, team: 0.2, traction: 0.1, financial: 0.1 },
  seed: { product: 0.25, market: 0.2, team: 0.15, traction: 0.25, financial: 0.15 },
  series_a: { product: 0.2, market: 0.15, team: 0.15, traction: 0.25, financial: 0.25 },
};

Investor Matching

typescript
// Reference: investor-agent edge function
interface InvestorMatch {
  investor_id: string;
  match_score: number;  // 0-100
  reasons: string[];    // Why they match
  signals: {
    stage_fit: boolean;
    industry_fit: boolean;
    check_size_fit: boolean;
    thesis_alignment: number;
  };
}

// Matching criteria
const matchCriteria = {
  stage: startup.stage,
  industry: startup.industry,
  geography: startup.location,
  check_size: startup.raising_amount,
  thesis_keywords: extractKeywords(startup.description),
};

Canvas Analysis

typescript
// Reference: lean-canvas-agent edge function
interface CanvasAnalysis {
  completeness: number;  // 0-100
  coherence: number;     // 0-100 (do sections align?)
  gaps: string[];        // Missing or weak sections
  suggestions: {
    section: string;
    current: string;
    suggested: string;
    reason: string;
  }[];
}

// Section validation rules
const validationRules = {
  problem: { min_length: 50, requires: ['pain_point', 'frequency'] },
  solution: { must_address: 'problem', avoid: ['feature_list'] },
  unique_value: { formula: 'For [X] who [Y], we [Z] unlike [W]' },
  unfair_advantage: { not_allowed: ['first_mover', 'passion', 'hard_work'] },
};

5. Best Practices Checklist

When Building Startup Features

  • Check if industry playbook exists for user's industry
  • Use stage-appropriate metrics and guidance
  • Reference YC/a16z best practices where applicable
  • Include industry-specific terminology
  • Validate against common failure patterns
  • Provide actionable recommendations, not just scores

When Accessing Playbooks

  • Always filter by is_active = true
  • Cache playbook data (update frequency: monthly)
  • Fall back to generic advice if industry not found
  • Use prompt_context to enhance AI responses

When Implementing Scoring

  • Use stage-appropriate weights
  • Provide breakdown, not just total score
  • Include specific recommendations
  • Compare to industry benchmarks where available
  • Explain score changes over time

6. Quick Reference

Edge Functions for Startup Features

FunctionPurposePlaybook Integration
health-scorerCalculate startup healthUses benchmarks
stage-analyzerDetermine/validate stageUses stage_checklists
investor-agentMatch and research investorsUses investor_expectations
lean-canvas-agentCanvas analysisUses decision_frameworks
pitch-deck-agentDeck generationUses narrative_arc, slide_emphasis
industry-expert-agentIndustry guidanceFull playbook access
compute-daily-focusDaily recommendationsUses stage_checklists

Database Tables

TablePurpose
industry_playbooksIndustry-specific knowledge
prompt_packsAI workflow templates
startupsUser startup data
health_scoresHistorical health scores
lean_canvasesBusiness model canvases

7. Examples

Example: Inject Industry Context into AI Prompt

typescript
async function buildPromptWithPlaybook(
  basePrompt: string,
  startupId: string
): Promise<string> {
  // Get startup's industry
  const { data: startup } = await supabase
    .from('startups')
    .select('industry')
    .eq('id', startupId)
    .single();

  // Get playbook
  const { data: playbook } = await supabase
    .from('industry_playbooks')
    .select('prompt_context, terminology, benchmarks')
    .eq('industry_id', startup.industry)
    .single();

  if (!playbook) return basePrompt;

  return `${basePrompt}

Industry Context (${startup.industry}):
${playbook.prompt_context}

Key Terminology:
${JSON.stringify(playbook.terminology, null, 2)}

Industry Benchmarks:
${JSON.stringify(playbook.benchmarks, null, 2)}`;
}

Example: Stage-Appropriate Task Generation

typescript
async function generateStageTasks(
  startupId: string
): Promise<Task[]> {
  const { data: startup } = await supabase
    .from('startups')
    .select('stage, industry')
    .eq('id', startupId)
    .single();

  const { data: playbook } = await supabase
    .from('industry_playbooks')
    .select('stage_checklists')
    .eq('industry_id', startup.industry)
    .single();

  const checklist = playbook?.stage_checklists?.[startup.stage] || [];

  return checklist.map(item => ({
    title: item.title,
    description: item.description,
    category: item.category,
    priority: item.priority,
    stage_relevant: true,
  }));
}

Related Skills:

  • /gemini - AI integration for startup features
  • /supabase - Database operations
  • /edge-functions - Serverless function patterns
  • /doc-coauthoring - Document generation

Related Prompts: