De la autor
Build a User Input Grid (UIG) for an AI product or feature, evaluate existing eval datasets against it, and propose new inputs to fill coverage gaps. Use this skill whenever someone asks to design an eval framework, audit a test set, build a "user input grid", "synthetic query matrix" or "SQM", improve dataset coverage, or assess whether their offline evals reflect what real users will actually send. Also trigger when they share a product domain + sample dataset and want to know what the dataset is missing, or when they're setting up evals from scratch for a new AI feature. Output is a markdown file (UIG framework + dataset evaluation + recommendations) saved to the current project directory.
Instalare
npx skills add Calibre-Labs/reforge-ai-evals --skill uig -a claude-code
Se instalează în .claude/skills/uig/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
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Verificări de siguranță pe SKILL.md
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De ce 83
aiqbench calculează scorul de încredere din semnale publice. Nu este un audit de securitate, așa că citește un skill înainte să-l instalezi.
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