Codex Grade Coding
Turn your AI agent into a senior engineer with strict task classification and verification-driven coding protocols.
Free
Works with the AI tools you already use
Claude Code
Cursor
Codex CLI
GitHub Copilot
Gemini CLI+17 moreClaude CodeCursorCodex CLIGitHub CopilotGemini CLI
VS Code
Windsurf
Manus+14 moreSee it in action
You say
Fix the intermittent race condition occurring during concurrent user logins in the Auth Provider. Keep the scope tight and prove the fix works.
Your agent does
TASK: Fix race condition in Auth Provider SCOPE: Narrow (Auth.ts only) VERIFICATION: Reproduced failure with concurrent login script. Verified fix with 100 iterations of 'npm test auth/'. RISK: Low. Change is isolated to the locking mechanism. RESIDUAL: Possible 50ms latency increase.
About this skill
Level up your agent's engineering discipline
Codex-Grade Coding is a high-performance protocol designed to transform standard AI agents into disciplined senior engineers. It solves the common problem of "drift" and "over-coding" by enforcing a strict operational framework that prioritizes task classification, scope control, and evidence-based verification.
What it does
Instead of jumping straight into code, this skill forces the agent to classify the task (Trivial, Standard, Risky, or Review) and select an appropriate "Verification Ladder" step. It constrains the agent to the narrowest viable change, preventing unnecessary refactors or "hallucinated cleanup" that often introduces bugs in complex codebases.
Why use this skill
While basic prompting might get the code written, Codex-Grade Coding ensures the work is proven. It is particularly effective for making smaller or less reliable models perform at a Much higher tier by providing a repeatable engineering bar. The output adheres to a strict "Final Answer Contract," making it easy for human developers to verify what was changed and why.
Supported workflows
- Bug Fixes: Mandatory reproduction steps before applying fixes.
- Refactoring: Forced proofs that behavior remains unchanged.
- Code Reviews: Findings prioritized by correctness and regression risk.
- Benchmarking: Includes a rubric to score agent performance on scope discipline and hallucination control.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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