Generate structured proof packages with dependency maps for ML/AI theorems.
npx skills add https://github.com/jkfee/Auto-Research --skill proof-writer-jkfee
Please help me install this Agent Skill. Skill: proof-writer Source: https://github.com/jkfee/Auto-Research/tree/main/skills/proof-writer Command: npx skills add https://github.com/jkfee/Auto-Research --skill proof-writer-jkfee
This Skill helps researchers and AI agents construct rigorous mathematical proofs for ML/AI theory, identify gaps, and convert informal sketches into verifiable arguments.
Provide a complete proof package for the given theorem and assumptions.
High-intent search queries and answers about installing and using this skill.
To write rigorous mathematical proofs for ML theory, provide exact claims, assumptions, and notation to generate a complete proof package with stepwise justifications and a dependency map ready for review.
Validating an informal proof sketch for ML theorems requires converting the sketch into verifiable arguments by identifying gaps, proposing corrected statements, and supplying stepwise justifications.
Yes, you can generate corrected claims when your formal proof has logical gaps by identifying missing steps and proposing corrected statements with the necessary stepwise justifications.
To generate a complete formal proof package, you must provide exact claims, assumptions, notation, and any informal sketch to output a structured document with a dependency map and stepwise justifications.
Proof validation works for lemmas, propositions, and corollaries in AI research by automating rigorous theorem drafting across math-heavy AI topics to produce verifiable arguments from your assumptions.
You should not use automated theorem drafting for ML/AI theory when you lack exact claims, assumptions, and notation, as the Skill requires these precise inputs to generate verifiable proof packages.
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