Automated deal scoring based on thesis alignment, market size, team, and traction metrics
Generates investment opportunity scores based on thesis alignment, market size, team quality, and traction metrics.
npx claudepluginhub a5c-ai/babysitterThis skill is limited to using the following tools:
The Deal Scoring Engine skill provides automated, consistent evaluation of investment opportunities against defined criteria. It generates composite scores based on thesis alignment, market opportunity, team quality, and business traction to support pipeline prioritization and investment decisions.
Input: Company data, metrics, team information
Process: Apply scoring models across dimensions
Output: Composite score, dimension scores, flags, recommendations
Input: Scoring criteria, weights, thresholds
Process: Update scoring model parameters
Output: Configured scoring model, validation results
Input: Deal scores, portfolio company scores
Process: Compare against portfolio at similar stage
Output: Relative ranking, percentile position, comparisons
Input: Historical deals and outcomes
Process: Analyze predictive accuracy, adjust weights
Output: Calibration report, recommended adjustments
| Dimension | Weight Range | Key Factors |
|---|---|---|
| Thesis Fit | 15-25% | Sector, stage, geography, strategy |
| Market | 20-30% | TAM, growth, competition, timing |
| Team | 25-35% | Experience, domain, completeness |
| Traction | 20-30% | Revenue, growth, unit economics |
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