Agent Orchestration Improve Agent
Refines agent workflows and capabilities through iterative feedback loops and automated optimization techniques.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add agent-orchestration-improve-agent npx -- -y @trustedskills/agent-orchestration-improve-agent
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"agent-orchestration-improve-agent": {
"command": "npx",
"args": [
"-y",
"@trustedskills/agent-orchestration-improve-agent"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill allows you to improve the performance of existing AI agents by providing feedback and guidance. It can analyze agent responses, identify areas for improvement, and suggest modifications to prompts or agent configurations. The goal is to iteratively refine agent behavior and achieve more desirable outcomes through targeted adjustments.
When to use it
- Debugging complex tasks: When an agent struggles with a multi-step task, this skill can help pinpoint the exact point of failure.
- Refining creative output: If you're using an agent for writing or art generation and want more specific stylistic changes, this skill can guide those adjustments.
- Improving accuracy in knowledge retrieval: When an agent provides inaccurate information, use this skill to correct its reasoning and improve future responses.
- Optimizing for efficiency: To reduce the number of calls needed to complete a task, refine prompts with feedback from this skill.
Key capabilities
- Response analysis
- Feedback generation
- Prompt modification suggestions
- Configuration adjustment recommendations
Example prompts
- "Analyze the agent's response and suggest improvements for clarity."
- "The agent made an error in its reasoning; provide feedback to correct it."
- "Suggest a prompt rewrite that will encourage more concise answers from the agent."
Tips & gotchas
This skill is most effective when used with agents that already have some level of functionality. It requires careful observation and interpretation of the agent's behavior to provide meaningful feedback.
Tags
TrustedSkills Verification
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Security Audits
| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
🌐 Community
Passed automated security scans.