Dspy Optimization
Automatically refines prompt engineering strategies to maximize AI model performance and output quality.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add dspy-optimization npx -- -y @trustedskills/dspy-optimization
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"dspy-optimization": {
"command": "npx",
"args": [
"-y",
"@trustedskills/dspy-optimization"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill optimizes the performance of AI agents using DispositioPy (dspy). It automatically adjusts agent parameters and configurations to improve response quality, reduce latency, and enhance overall efficiency. The optimization process is designed to be automated and requires minimal manual intervention.
When to use it
- Slow Agent Responses: If your dspy-based AI agent takes too long to generate responses.
- Suboptimal Output Quality: When the agent's outputs are not as accurate, relevant, or helpful as desired.
- Resource Intensive Agents: To reduce the computational resources (CPU/GPU) required by a dspy agent.
- Automated Tuning: For scenarios where you want to continuously improve your AI agent’s performance without manual adjustments.
Key capabilities
- Automatic parameter tuning for dspy agents.
- Performance optimization of response quality and latency.
- Resource usage reduction.
- Integration with DispositioPy (dspy) framework.
Example prompts
- "Optimize my agent to reduce its average response time."
- "Tune the parameters of my 'creative_writer' dspy agent for higher-quality stories."
- "Can you improve the accuracy of my question answering agent?"
Tips & gotchas
This skill requires a working DispositioPy (dspy) environment. Ensure your agent is properly configured within dspy before attempting optimization.
Tags
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Security Audits
| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
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