- Home
- Skills
- Testing & Debugging
- LLM Evaluation Contamination Boundary Check
More screenshots
Works with the AI Agents you already use
LLM Evaluation Contamination Boundary Check
Screen benchmark and evaluation pipelines for inadvertent test-set leakage into prompts, exemplars and retrieval sources.
$1
About this skill
Screen benchmark and evaluation pipelines for inadvertent test-set leakage into prompts, exemplars and retrieval sources.
What it checks:
- trace benchmark sample exposure routes
- fingerprint suspect exact and near duplicates
- separate public overlap from privileged test access
- prescribe clean holdout re-evaluation
Deliverables:
- contamination map
- evidence-tagged suspect set
- clean evaluation protocol
Typical case: A held-out exam question turns out to be copied into a retrieval examples bundle used at inference.
Runtime: Cursor Skill
Find more skills like this on the Claude Skills Marketplace, the Codex Skills Marketplace and the Gemini Skills Marketplace, or browse Claude Skills for Testing & Debugging.
How to use
- 1
Connect your agent to the Agensi MCP
Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup
- 2
Sign in to Agensi
Your agent shows a sign-in link. Sign in and click Allow.
- 3
Ask for what you need
Your agent loads this skill and uses it on your task. It always asks before buying a skill.
Reviews
No reviews yet
Be one of the first to try it. Every listed skill goes through the trust checks below.
Security scanned
Checked by our 8-point scan before listing
Fresh listing
Recently published to Agensi
Money-back guarantee
Doesn't do what its page promises? You get your money back.
Trust & safety
Security scan
Security scan passed 1 month ago
Permissions
No special permissions declared or detected