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skillboardRigorously and honestly assess a NEW or proposed covariance / correlation / precision estimator, or a new covariance scoring rule, using precise. Use when someone proposes, asks to evaluate, or wants to compare a covariance methodology. Covers implementing it to the contract, conformance, benchmarking against the registry, out-of-sample validation, and statistically defensible inference.
Assess a new covariance/correlation methodology A protocol for turning "here's a covariance idea" into a defensible verdict. Work the steps in order; stop early only if a step fails. Install: (the scripts use scikit learn and ). 0. Classify the method first Estimator (produces a matrix) vs assessor (scores a matrix)? Different paths below. Online (updatable per observation) or batch ? precise is an online library; a batch method can still be wrapped, but say so. Does it target the covariance ,…
Full body not shown for this license – view the source on GitHub →Copy a source-pinned command for your client. You run it yourself.
Destination: .claude/skills/assess-covariance-method · pinned to the source commit
git clone https://github.com/microprediction/precise.git
cd precise
git checkout d89c883e91138546a785c7c1a81c0eba5433b2f4
mkdir -p ".claude/skills/assess-covariance-method"
cp -r ".claude/skills/assess-covariance-method" ".claude/skills/assess-covariance-method"Review the source before running. This copies files into your project; it is not a one-click install and does not verify runtime safety.
Scanner static-checks@0.1.0 · commit d89c883e9113. Static checks cannot prove runtime safety – review the source and the exact diff before installing. How checks work.
Instructs shell/process/package operations that run commands on the host.
Evidence: pip install· fingerprint 7944ec554efca445