Construct and verify mathematical proofs for ML/AI theory.
npx skills add https://github.com/THUFanZd/Sewed_pipeline --skill proof-writer-thufanzd
Please help me install this Agent Skill. Skill: proof-writer Source: https://github.com/THUFanZd/Sewed_pipeline/tree/main/.agents/skills/proof-writer Command: npx skills add https://github.com/THUFanZd/Sewed_pipeline --skill proof-writer-thufanzd
Writes mathematically honest proofs for ML/AI theory, including filling in missing proof steps, formalizing a proof sketch, 补全证明, 写证明, or determining whether a claimed proof can actually be completed under the stated assumptions.
Provide a complete Proof Package for the requested theorem following the required file structure and rigorous validation steps.
High-intent search queries and answers about installing and using this skill.
To write rigorous mathematical proofs for ML theory, you can generate a complete Proof Package containing explicit assumptions, notation, numbered steps, and justifications for nontrivial implications. This automates proof construction and verification for theorems or lemmas.
To formalize a proof sketch and fill in missing steps, provide the sketch to generate a structured proof document with a dependency map and rigorous validation. This completes the proof package by detailing every nontrivial implication required for peer review.
Yes, you can assess if a claimed theorem is provable under the stated assumptions by classifying the claim as provable as stated, provable after weakening, or not justified. This generates a blockage report detailing open risks and edge cases.
The best way to structure a proof for audit and peer review is to produce a Proof Package with explicit status, a dependency map, and a dedicated Open Risks section. This format ensures every nontrivial implication has explicit justification.
Yes, this proof-writing approach works for lemmas and corollaries within project codebases. It automates the rigorous construction of mathematical proofs for ML/AI theory, directly integrating the formalized proof steps and notation into your existing project files.
dogekikiGenerate structured mathematical proofs with dependency mapping and status classification.
Wenwen555Draft dependency-aware mathematical proof packages for ML/AI theorems.
HeXiao-55Generate a structured proof package with assumptions, notation, and dependency map.
satsuki-64Draft rigorous mathematical proofs for ML/AI theory from formal claims and assumptions.
