ml-metacognition

Name: ml-metacognition
Availability: InStock
Author: lofibrainwav

Community

Self-reflection optimization for ML with math proofs.

Education & Research #feedback #self-reflection #metacognition #sympy #convexity

Authorlofibrainwav

Version1.0.0

Installs0

System Documentation

What problem does it solve?

This Skill enhances machine-learning model metacognition: a feedback loop with convexity proofs to improve self-reflection over time.

Core Features & Use Cases

Feedback integration: Incorporate user feedback into model evaluation.
Convexity proof: Sympy-based justification for convergence properties.
2nd derivative optimization: Advanced optimization for performance gains.

Quick Start

result = await metacognition.run(input_batch)

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: ml-metacognition
Download link: https://github.com/lofibrainwav/AFO_Kingdom/archive/main.zip#ml-metacognition

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.

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