Enforce evidence-based reasoning and safety gates for AI modifications.
npx skills add https://github.com/sstklen/yes.md --skill yes-zh
Please help me install this Agent Skill. Skill: yes-zh Source: https://github.com/sstklen/yes.md/tree/main/skills/yes-zh Command: npx skills add https://github.com/sstklen/yes.md --skill yes-zh
This Skill acts as an AI governance engine, ensuring AI assistants operate safely, evidence-based, and thoroughly by enforcing strict rules and preventing common AI bad habits like guessing, deflecting, and superficial fixes.
Use the yes-zh skill to ensure the AI follows evidence-based rules and safety gates before making any code changes.
High-intent search queries and answers about installing and using this skill.
To enforce evidence-based reasoning in an AI assistant, you need an AI governance engine that prevents claims without data. It catches and corrects common AI bad habits like guessing and superficial fixes by requiring strict verification before reaching conclusions.
An AI governance engine is a multi-layered system that enforces AI safety, evidence-based reasoning, and thoroughness. You need it for structured debugging when an AI assistant repeatedly fails and requires increasing levels of self-inspection to resolve complex issues.
To mandate backups and impact analysis before code modifications, implement safety gates within your AI workflow. These gates enforce pre-deployment checks, verify the blast radius of changes, and ensure all modifications are backed up and tested before completion.
Yes, this AI governance framework works without external dependencies. It operates as a standalone skill that enforces strict rules and safety gates inherently, requiring no additional components or libraries to manage AI behavior and modifications.
The best way to structure professional handoffs for AI coding tasks is using a governance framework that ensures evidence-based rules and safety gates are met. This guarantees all modifications are verified, tested, and documented before transferring the task.
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