Formalize ML/AI theorem proofs into structured PROOF_PACKAGE.md files.
npx skills add https://github.com/xqinag/ARIS-new --skill proof-writer-xqinag
Please help me install this Agent Skill. Skill: proof-writer Source: https://github.com/xqinag/ARIS-new/tree/main/skills/proof-writer Command: npx skills add https://github.com/xqinag/ARIS-new --skill proof-writer-xqinag
Writes mathematically honest proofs for ML/AI theory. When asked to prove a theorem, lemma, proposition, or corollary, fills in missing proof steps and formalizes a proof sketch.
Summarize the exact theorem and assumptions, then request a full Proof Package with a dependency map and steps.
High-intent search queries and answers about installing and using this skill.
To formalize a proof sketch for ML theory, provide the explicit theorem statement, assumptions, and notation. The tool fills missing steps and generates a structured PROOF_PACKAGE.md with a dependency map and stepwise justifications.
Writing rigorous proofs for ML lemmas requires normalizing the exact claim, identifying logical gaps, and generating step-by-step justifications. This process outputs a complete formal argument structured for reproducible research workflows.
Yes, you can fill gaps in proposition proofs by supplying your existing sketch. It analyzes the provided assumptions, suggests corrections or blockage reports, and outputs a fully justified formal argument.
Yes, providing exact assumptions and notation is required. Formalizing a corollary proof depends on explicit statements of the claim and user-provided sketches to successfully generate a complete, mathematically honest proof package.
Limitations arise when the initial theorem statement lacks explicit claims or assumptions. If the sketch has unresolvable logical gaps, the process outputs a blockage report detailing the missing dependencies rather than forcing a complete formal argument.
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