Scoutqa Test
Evaluates question answering models using a provided dataset, generating performance metrics and identifying areas for improvement.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add scoutqa-test npx -- -y @trustedskills/scoutqa-test
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"scoutqa-test": {
"command": "npx",
"args": [
"-y",
"@trustedskills/scoutqa-test"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
The scoutqa-test skill is designed to test and evaluate AI agent capabilities through structured questioning. It enables users to assess how well an AI can understand, reason, and respond to complex prompts in a controlled environment.
When to use it
- To validate the accuracy of an AI's responses before deployment
- During development to identify gaps in reasoning or knowledge
- For benchmarking performance across different AI models
Key capabilities
- Structured testing with predefined question sets
- Evaluation of response quality and consistency
- Integration with AI agent workflows for iterative improvement
Example prompts
- "Explain the process of photosynthesis in simple terms."
- "What are three key differences between Python and JavaScript?"
- "Analyze this code snippet and identify any potential bugs."
Tips & gotchas
- Ensure test questions are relevant to the AI's training domain for accurate results.
- Use a variety of question types (e.g., factual, analytical) to get a well-rounded evaluation.
Tags
TrustedSkills Verification
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Security Audits
| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
🏢 Official
Published by the company or team that built the technology.