advanced-evaluation
advanced-evaluation是一款data方向的AI技能，核心价值是This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise compari，可用于解决开发者在data领域的实际问题，帮助用户提升效率、自动化重复任务或优化工作流。
This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise compari
mkdir -p ./skills/advanced-evaluation && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/advanced-evaluation/SKILL.md -o ./skills/advanced-evaluation/SKILL.mdRun in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise compari
🎯 Best For
- Claude users
- Data professionals
- Analytics teams
- Researchers
💡 Use Cases
- Data pipeline auditing
- Query optimization
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply advanced-evaluation to Your Work
Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.
- 4
Review and Refine
Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.
❓ Frequently Asked Questions
How do I install advanced-evaluation?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/advanced-evaluation/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Ignoring data quality
AI analysis inherits all data quality issues — profile your data first.