startup-risk-radar

by conn-ho

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SKILL.md About

---
name: startup-risk-radar
description: Evaluate startup ideas, business models, and product strategies against the 7 deadly failure antipatterns extracted from 1,749 dead startups that burned $535B+. Use when the user is evaluating a startup idea, planning a new product, reviewing a business model, assessing competitive positioning, checking unit economics, or asking "will this work?" Also trigger when the user mentions startup risk, failure patterns, competitive moat, unit economics, burn rate, market need validation, regulatory risk, founder conflict, product-market fit concerns, or pivot decisions. Provides structured risk assessment, red flag identification, and actionable recommendations based on real failure data.
---

# Startup Risk Radar — Failure Pattern Analysis

Framework from 1,749 dead startups and $535.4B burned capital. Source: loot-drop.io

## The 7 Antipatterns

| # | Antipattern | Emoji | Deaths | Capital Burned | Median Life | % of All |
|---|-------------|-------|--------|---------------|-------------|----------|
| 1 | The Hallucination (No Market Need) | 🔮 | 203 | $14.9B | 3 yr | 11.6% |
| 2 | The Bonfire (Ran Out of Cash) | 🔥 | 205 | $285.0B | 4 yr | 11.7% |
| 3 | The Civil War (Founder Conflict) | ⚔️ | 13 | $2.5B | 4 yr | 0.7% |
| 4 | The Crushed (Competition) | 🏴 | 901 | $43.5B | 3 yr | 51.5% |
| 5 | The Lemon (Product/Tech Failure) | 🍋 | 70 | $15.7B | 5 yr | 4.0% |
| 6 | The Outlaw (Legal/Regulatory) | ⚖️ | 86 | $67.9B | 7 yr | 4.9% |
| 7 | The Math Problem (Unit Economics) | 📉 | 269 | $105.8B | 5 yr | 15.4% |

## How to Use This Skill

### When evaluating a startup idea or business model:

1. Read `references/antipatterns.md` for detailed pattern descriptions, mechanics, cognitive traps, and red flags
2. Read `references/chain-reactions.md` for how antipatterns cascade into each other
3. Score the idea against all 7 antipatterns using the assessment questions below
4. Identify the most likely failure cascade
5. Provide actionable recommendations

### Quick Assessment (7 Questions)

For each antipattern, evaluate the startup on a 3-point scale: 🟢 Low risk / 🟡 Medium risk / 🔴 High risk

1. **🔮 Hallucination**: Do potential customers pull out their wallets unprompted, or just say "sounds interesting"?
2. **🔥 Bonfire**: If fundraising stopped tomorrow, could you reach profitability in 6 months?
3. **⚔️ Civil War**: Do co-founders have a clear decision-making process for disagreements?
4. **🏴 Crushed**: Is your roadmap driven by unique customer insights or by matching competitor features?
5. **🍋 Lemon**: Can your core tech deliver at production scale without manual intervention?
6. **⚖️ Outlaw**: Would full regulatory compliance destroy your unit economics?
7. **📉 Math Problem**: At current fully-loaded costs + 25% improvement, do margins exceed 20%?

### Output Format

Structure your analysis as:

```
## Startup Risk Assessment: [Name/Idea]

### Antipattern Scorecard
[Score each of 7 antipatterns: 🟢/🟡/🔴 with brief justification]

### Primary Risk: [Most dangerous antipattern]
[Detailed analysis of the most likely failure mode]

### Cascade Risk: [Chain reaction path]
[How the primary risk could trigger secondary failures]

### Red Flags Detected
[List specific red flags from the antipattern framework]

### Recommendations
[Actionable steps to mitigate identified risks]
```

### Key Statistics by Sector

Most dangerous sectors (by total failures):
- Communication Services: 444 failures
- Consumer: 414 failures  
- Information Technology: 402 failures
- Financials: 156 failures

Most common cause of death:
- Competition (51.5%) — over half of all startups die from being outgunned
- Unit Economics (15.4%) — the math never worked
- Ran Out of Cash (11.7%) — spending as if revenue is a formality
- No Market Need (11.6%) — building for a customer that doesn't exist

_meta.json Metadata

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  "slug": "startup-risk-radar",
  "version": "1.0.0"
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