Math Auditor
CommunityRigorous math verification for AI research.
Education & Research#code validation#mechanistic interpretability#research rigor#math verification#statistical audit#R_V metric
AuthorAmitabhainArunachala
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill provides expert-level mathematical and statistical verification for mechanistic interpretability research, ensuring the rigor and validity of claims, especially concerning metrics like R_V and consciousness geometry.
Core Features & Use Cases
- Mathematical Derivation Check: Verifies the correctness of mathematical formulas and derivations.
- Statistical Methodology Audit: Audits statistical tests, effect sizes, and sample size justifications.
- Code-Theory Match: Ensures that the implementation in code precisely matches the mathematical definitions.
- Use Case: Before publishing research on a new interpretability metric, use this Skill to mathematically audit the metric's definition, its statistical properties, and its implementation in the codebase.
Quick Start
Use the Math Auditor skill to verify the R_V metric calculation in the file src/metrics/rv.py.
Dependency Matrix
Required Modules
numpyscipytorch
Components
scriptsreferences
💻 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: Math Auditor Download link: https://github.com/AmitabhainArunachala/clawd/archive/main.zip#math-auditor Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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