taylorsatula/TeaLeaves

End-to-end pipeline for seeing how LLMs actually process your prompts. Capture attention across every layer, render heatmaps and cooking curves, compare variants with evidence — not vibes.

42
Stars
4
Forks
24.8
Radar Score
Stable
Momentum

Scoring Breakdown

Impact14.6
Velocity21.6
Health45.7

Growth Metrics

7-Day Stars
+0
30-Day Stars
+0
Acceleration
x
Language
Python

Why it ranks

Modest but positive momentum.

LLM FrameworksTop 92% globally

🛡️ Enterprise Readiness & Commercial Safety

Organic Growth
95%
High Confidence
Growth pattern looks organic.
License
Unlicensed / Custom
Review license terms carefully before commercial adoption.
Health Grade
B
Based on maintenance, issue response, and release cadence.
Radar Score
24.8
Composite of Impact, Velocity, and Health.
Disclaimer: This is an automated heuristic assessment based on public GitHub signals. Always perform your own security audit, dependency review, and legal compliance check before production deployment.

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