llm-evaluation
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.
75
66%
Does it follow best practices?
Impact
91%
1.75xAverage score across 3 eval scenarios
Passed
No findings from the security scan
Fix and improve this skill with Tessl
tessl review fix ./tests/ext_conformance/artifacts/agents-wshobson/llm-application-dev/skills/llm-evaluation/SKILL.mdThe canonical home for this skill is llm-evaluation in wshobson/agents
| Run | Type | Date | Status |
|---|---|---|---|
baseline vs usage-spec With / without contextCompleted | With / without context | Completed |
Eval run
019cc843-1af5-7378-9aac-22ac71e11918
Run
Stats are not available yet
The run is available. Its result stats will appear here when they are ready.
- Evaluated
- Agent
- Claude Code
- Model
- Claude Sonnet 4.6
Table of Contents
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