Advanced Evaluation

🌐Community
by chakshugautam · vlatest · Repository

This skill deeply analyzes text for nuanced sentiment, bias, and factual accuracy, boosting reliable insights & decision-making.

Install on your platform

We auto-selected Claude Code based on this skill’s supported platforms.

1

Run in terminal (recommended)

terminal
claude mcp add chakshugautam-advanced-evaluation npx -- -y @trustedskills/chakshugautam-advanced-evaluation
2

Or manually add to ~/.claude/settings.json

~/.claude/settings.json
{
  "mcpServers": {
    "chakshugautam-advanced-evaluation": {
      "command": "npx",
      "args": [
        "-y",
        "@trustedskills/chakshugautam-advanced-evaluation"
      ]
    }
  }
}

Requires Claude Code (claude CLI). Run claude --version to verify your install.

About This Skill

What it does

This skill, chakshugautam-advanced-evaluation, provides a mechanism to evaluate and refine AI agent performance. It allows users to assess an agent's output against specific criteria and provide feedback, ultimately improving its capabilities. The tool is designed for iterative improvement of AI agents through structured evaluation processes.

When to use it

  • Debugging Agent Behavior: Identify why an agent isn’t performing as expected in a particular scenario.
  • Refining Task Completion: Improve the quality and accuracy of an agent's output on complex tasks.
  • Evaluating Different Approaches: Compare the effectiveness of various prompting strategies or agent configurations.
  • Measuring Progress Over Time: Track improvements to an AI agent’s performance after training or adjustments.

Key capabilities

  • Evaluation against specific criteria
  • Feedback provision for iterative improvement
  • Assessment of agent output quality and accuracy
  • Comparison of different approaches

Example prompts

  • "Evaluate the agent's response to this prompt: [prompt text] using these criteria: [criteria list]"
  • "Provide feedback on the agent’s performance in completing this task: [task description]."
  • "Compare the outputs of two agents given the same input and rate them based on [metric]."

Tips & gotchas

The effectiveness of this skill depends heavily on providing clear and well-defined evaluation criteria. Vague or subjective criteria will lead to less actionable feedback for the AI agent.

Tags

🛡️

TrustedSkills Verification

Unlike other registries that point to live repositories, TrustedSkills pins every skill to a verified commit hash. This protects you from malicious updates — what you install today is exactly what was reviewed and verified.

Security Audits

Gen Agent Trust HubPass
SocketPass
SnykPass

Details

Version
vlatest
License
Author
chakshugautam
Installs
3

🌐 Community

Passed automated security scans.