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    codex-grade-coding

    by Roy Yuen

    Turn your AI agent into a senior engineer with strict task classification and verification-driven coding protocols.

    Updated Apr 2026
    0 installs

    Free

    One-time purchase · Own forever

    ⚡ Also available via Agensi MCP — your AI agent can load this skill on demand via MCP. Learn more →

    Included in download

    • Downloadable skill package
    • Instant install

    See it in action

    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.

    📖 Learn more: Best Frontend & Design Skills for Claude Code →

    Use Cases

    • Enforce senior-level coding standards on weaker AI models
    • Prevent scope creep and unnecessary code changes during refactors
    • Standardize bug reports with mandatory verification evidence
    • Systematically benchmark and score AI coding performance

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    Security Scanned

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    Tags

    software-engineering
    code-quality
    debugging
    refactoring
    system-design

    Creator

    Roy Yuen

    Frequently Asked Questions

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