deal-scoring-engine

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Automated deal scoring based on thesis alignment, market size, team, and traction metrics

AI & Automation 814 stars 53 forks Updated today MIT

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Skill Content

# Deal Scoring Engine ## Overview 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. ## Capabilities ### Thesis Alignment Scoring - Match opportunities against fund investment thesis - Sector, stage, and geography fit assessment - Strategic priority alignment scoring - Anti-thesis and exclusion criteria flagging ### Market Opportunity Assessment - TAM/SAM/SOM scoring based on market data - Market growth rate and timing assessment - Competitive intensity evaluation - Regulatory and macro environment scoring ### Team Evaluation Scoring - Founder background and experience assessment - Domain expertise and market knowledge scoring - Team completeness and capability gaps - Track record and references scoring ### Traction and Metrics Scoring - Revenue and growth rate benchmarking - Unit economics (LTV/CAC, margins) scoring - Engagement and retention metrics assessment - Capital efficiency and burn rate evaluation ### Composite Score Generation - Weighted composite scoring with configurable weights - Stage-appropriate scoring models (seed vs. growth) - Sector-specific scoring adjustments - Historical score calibration against outcomes ## Usage ### Score New Deal ``` Input: Company data, metrics, team information Process: Apply s...

Details

Author
a5c-ai
Repository
a5c-ai/babysitter
Created
4 months ago
Last Updated
today
Language
JavaScript
License
MIT

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