startup-evaluation

name	startup-evaluation
description	Evaluate startup health using entrepreneurship, VC, and execution frameworks. Use when assessing a startup idea, company, pitch, due diligence target, fundraising readiness, or business model health.
version	1.2
updated	2026-05-24
assumes	The idea or company can be assessed through stage, customer, market, product, team, traction, capital, and risk evidence.
conflicts_with	Do not treat founder claims, TAM slides, or investor narratives as verified facts; use deep-research or verify-before-claim for evidence checks.

Startup Evaluation

Evaluate the health of a startup, not just the attractiveness of its pitch.

This skill combines:

• MIT Disciplined Entrepreneurship: beachhead, customer, value, business model, validation
• Timmons model: opportunity x team x resources dynamic fit
• VC 5T model: Team, Target Market, Tech/Product, Traction, Terms
• PMF and pretotyping: behavior evidence before build effort
• Efficiency models: define the question, use MECE, test assumptions cheaply

Usage Template

Prompt

Use startup-evaluation on this company/idea.
Assess startup health, evidence quality, red flags, fundraising readiness, and the next cheapest validation step.

Use Case

• Founder wants a health check before building, hiring, or fundraising.
• Investor wants a due diligence memo or pass/lean-in decision.
• Team wants to identify the one constraint limiting progress.

Expected Result

• A structured startup health memo with scores, evidence, risks, and validation experiments.

Output Example

• Stage: Seed. Health score: 62/100. Verdict: promising but not Series A ready. Top constraint: weak retention evidence. Next test: 20-customer paid pilot with D30 retention threshold.

Verification Case

• The output separates facts, assumptions, and opinions; every score cites evidence or marks missing evidence.

Verified Effect

• Startup enthusiasm becomes a health dashboard, risk register, and concrete validation plan.

Success Metrics

• Stage, startup type, and evaluation objective are explicit.
• Scores distinguish evidence-backed health from narrative confidence.
• The memo identifies top constraint, fatal risks, runway status, and next cheapest test.
• VC-scale companies are judged by power-law upside; bootstrapped companies are judged by cashflow and durability.

When to Use

• "Evaluate this startup."
• "Is this business healthy?"
• "Should I invest / join / keep building / fundraise?"
• "Review my pitch deck or startup idea."
• "What is the next validation experiment?"

Startup Health Model

Use this equation as the mental model:

Startup Health =
  Opportunity quality
  x Team quality
  x Evidence momentum
  x Capital discipline
  x Learning velocity
  - Fatal risks

Do not average away a fatal flaw. A brilliant market with no reachable customer, no team fit, or six weeks of runway is unhealthy.

Step 1: Classify the Case

Before scoring, classify:

Field	Options
Stage	idea, pre-seed, seed, Series A, growth, mature
Startup type	lifestyle/SME, innovation-driven, VC-scale, hard tech, AI-native
Evaluation lens	founder health check, investor due diligence, fundraising readiness, pivot decision
Evidence state	narrative only, interviews, behavior, payment, retention, repeatable growth

If data is missing, continue with assumptions and mark confidence low.

Step 2: Evidence Ladder

Rank claims by evidence quality:

Level	Evidence	Weight
0	Founder belief, TAM slide, friend feedback	very weak
1	Customer interviews about past behavior	weak
2	Landing page, waitlist, demo usage	moderate
3	Paid pilot, preorder, signed LOI, repeated use	strong
4	Retention, expansion, organic referral, healthy unit economics	very strong

Quotes and intentions do not prove demand. Payment, repeated usage, retention, and referral are stronger.

Step 3: Score Startup Health

Default weights. Adjust only when stage or startup type clearly requires it.

Dimension	Weight	Healthy signal	Red flag
Customer pain and beachhead	15	narrow painful use case, reachable buyer, urgent workflow	vague user, nice-to-have pain
Market and timing	15	large/growing market or focused profitable niche, clear timing window	TAM-only logic, market too early/late
Value proposition and 10x	15	10x better, 1/10 cost, or new capability	marginal improvement
PMF and traction	15	retention, payment, pull, repeatable channel	paid growth only, high churn, weak usage
Business model and unit economics	10	LTV/CAC > 3, clear pricing, gross margin path	CAC unknown, payback too long
Team and governance	15	founder-market fit, complementary roles, written equity/decision rules	solo gaps, cofounder conflict, weak recruiting
Capital and runway	10	12-18 month runway, milestone-based spend, financing plan	<6 month runway, unfocused burn
Moat and risk control	5	data, network, distribution, regulatory or execution moat	easily copied, platform/model dependency

Score each dimension:

0 = absent
1 = narrative only
2 = weak signal
3 = plausible but incomplete
4 = evidence-backed
5 = strong and repeatable

Final score:

Score	Status	Meaning
80-100	Healthy	Scale or fundraise if risks are bounded.
65-79	Promising	Continue, but fix the top constraint before major spend.
50-64	Fragile	Narrow scope and validate before hiring/fundraising.
0-49	Unhealthy	Pivot, pause, or redesign assumptions.

Step 4: VC 5T Cross-Check

For VC-backed or investor-facing evaluations, add a 5T view:

5T	Question
Team	Why this team? What unfair insight or execution proof exists?
Target Market	Can this become a power-law outcome, not just a good business?
Tech/Product	Is there defensibility beyond using current tools?
Traction	Is growth pulled by customers and retention, not only paid push?
Terms	Does valuation, dilution, and round structure leave room for returns?

Use the 5T view to decide whether the company is venture-scale. A healthy bootstrapped company can still be a poor VC investment.

Step 5: AI-Native and Hard-Tech Addendum

Use when relevant:

Question	Why it matters
Is this Type 1, 2, or 3 AI?	Tools on existing software, replacement software, or software becoming labor have different TAM and pricing logic.
Does the product improve 10-40% or 10-40x?	VC outcomes need step-change value, not small convenience.
What remains if code or models get cheaper?	Moat must move to data, workflow, distribution, trust, regulation, or physical execution.
Is there product surplus?	Products built for the next model can fail before users adopt them.
Are hardware, supply chain, regulation, or deployment loops bottlenecks?	Hard-tech health depends on non-software execution constraints.

Step 6: Runway and Financing Health

Use these thresholds:

Metric	Green	Yellow	Red
Runway	18+ months	6-18 months	<6 months
Fundraising start	before 12 months runway	6-12 months	after crisis starts
LTV/CAC	3-5+	1-3	<1 or unknown at scale
CAC payback	<12 months	12-18 months	>18 months
Burn focus	tied to next milestone	mixed	vanity hiring/spend

Capital should buy evidence for the next milestone. Spending that does not reduce the top uncertainty is unhealthy.

Step 7: Diagnose the Constraint

Name one primary constraint:

Constraint	Typical fix
No painful problem	customer discovery and problem pivot
Wrong beachhead	segment narrower by buyer, workflow, urgency
Weak value proposition	quantify before/after value and 10x wedge
No behavior evidence	pretotype, paid pilot, concierge MVP
Weak retention	reduce scope, improve core workflow, delay scale
Team gap	recruit missing builder/seller/operator, clarify equity and decisions
Capital risk	cut burn, milestone fundraising, smaller experiment
Moat risk	build data loop, distribution edge, workflow lock-in, trust layer

Step 8: Output Format

Return:

## Startup Health Memo

Stage / type / lens:
Verdict:
Health score:
Confidence:

### Evidence Ledger
Facts:
Assumptions:
Missing evidence:

### Scorecard
| Dimension | Score | Evidence | Risk |

### Top Constraint
...

### Red Flags
...

### Fundraising Readiness
...

### Next Cheapest Test
Hypothesis:
Experiment:
Metric:
Decision rule:
Cost/time:

### 30-Day Operating Focus
...

Quality Gates

• Stage, type, and lens are explicit.
• Facts, assumptions, and missing evidence are separated.
• Health score uses the scorecard and does not hide fatal risks.
• VC-scale and bootstrapped-health judgments are not conflated.
• Customer pain, beachhead, PMF, unit economics, team, runway, and moat are covered.
• Top constraint is singular and actionable.
• Next cheapest test has a metric, threshold, cost/time box, and decision rule.
• Final verdict names residual uncertainty.

Anti-Patterns

• Treating a large TAM as proof of opportunity.
• Scoring a startup from pitch quality rather than customer behavior.
• Averaging high team quality with zero demand evidence.
• Recommending fundraising before knowing the milestone capital will prove.
• Calling an AI wrapper defensible without data, distribution, workflow, or trust moat.
• Giving many generic suggestions instead of one constraint and one next test.

Connections

• [[wiki/concepts/创业基础框架]] — Timmons opportunity x team x resources
• [[wiki/concepts/创业机会识别]] — opportunity sources, beachhead, TAM/SAM/SOM
• [[wiki/concepts/产品市场契合]] — MVP, retention, payment, referral
• [[wiki/concepts/创业融资]] — runway, LTV/CAC, fundraising stages
• [[wiki/concepts/创业团队建设]] — founder fit, complementary roles, equity rules
• [[wiki/concepts/顶级VC评估框架]] — 5T, TOPSCAN, T2D3
• [[maps/创业知识库]] — entrepreneurship system map
• [[maps/VC与一级投资知识库]] — investor evaluation map
• [[maps/效率思维与模型]] — hypothesis-driven, MECE, cheap tests