Results for “llm-coding”

Guide AI coding work toward simple implementations, focused edits, and explicit assumptions. Use it when writing, reviewing, or refactoring code to keep changes tied to the request and define success through tests or other concrete checks.

• Keeping bug fixes limited to the necessary code
• Simplifying code that has become overcomplicated
• Making implementation assumptions explicit

Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.

The English summary is being prepared. Showing the original description.

Behavioral guardrails to reduce common LLM coding mistakes with a caution-first approach.

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Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.

The English summary is being prepared. Showing the original description.

Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.

The English summary is being prepared. Showing the original description.