qa-agent-testing
SolidQA harness for LLM agents: scenario suites, flake controls, tool sandboxing, LLM-as-judge scoring, and regression protocols.
Install
Quality Score: 83/100
Skill Content
Details
- Author
- vasilyu1983
- Repository
- vasilyu1983/AI-Agents-public
- Created
- 9 months ago
- Last Updated
- 1 weeks ago
- Language
- Python
- License
- MIT
Integrates with
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agent-evaluation
Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliability, test agent.
agent-evaluation
Evaluate LLM agents and tool-using workflows—task success, tool accuracy, latency/cost, safety, and regression suites. Use when shipping agent features, comparing prompts/models, or debugging agent failures.