Audit LLM-generated code blocks against four failure modes before deployment.
npx skills add https://github.com/cropsgg/skills --skill karpathy-rules
Please help me install this Agent Skill. Skill: karpathy-rules Source: https://github.com/cropsgg/skills/tree/main/skills/engineering/karpathy-rules Command: npx skills add https://github.com/cropsgg/skills --skill karpathy-rules
Encode and enforce four critical gate checks to prevent unsafe or misleading code blocks in AI-generated outputs.
Run Gate 1–4 verification for every code block; fix failures until all gates pass.
High-intent search queries and answers about installing and using this skill.
To audit LLM-generated code blocks, apply four verification gates checking for hallucinated APIs, over-engineering, missing error handling, and unverified assumptions to ensure outputs are production-ready and safe.
The best way to verify AI-generated code is applying gate checks against four failure modes: hallucinated APIs, unnecessary abstractions, missing IO error handling, and unverified environment assumptions before deployment.
Use a verification gate to audit code blocks and ensure robust error handling is present for IO, network, and async operations, preventing runtime failures in production-like contexts.
Yes, one of the four audit gates specifically checks for over-engineering by verifying code blocks to avoid unnecessary abstractions and favor simple, direct solutions.
Apply a verification gate to check unverified assumptions by validating environment facts, paths, and versions against the existing codebase to ensure reproducible and safe outputs.
Yes, you can integrate these four gates into a code-generation workflow to run verification steps and reproducible checks, ensuring every block passes audits before deployment.
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