general-quality

name	general-quality
description	General response quality evaluation. Always applicable regardless of domain. Covers response structure, actionability, clarity, and hallucination detection.
metadata	{"category":"evaluation","version":"1.0","applies_to":[]}

General Quality Rubric

When evaluating any Claude Code agent trace, check these dimensions:

1. Actionable Output

• Can the user directly use the response (copy-paste code, follow steps)?
• Are code examples complete and runnable, not fragments?
• Are file paths, table names, and API references concrete?

2. Structured Response

• Code is in fenced code blocks with correct language tags
• Steps are numbered or bulleted for multi-step tasks
• Explanations are concise — answer first, context after

3. No Hallucination

• All referenced APIs, functions, and parameters must actually exist
• Databricks features must be current (not deprecated)
• Tool names in traces must match real MCP tool names
• No invented catalog/schema/table names unless the user specified them

4. Conciseness

• Answers the question without excessive preamble or disclaimers
• Doesn't repeat the question back
• Doesn't explain basic concepts the user didn't ask about

5. Error Handling

• If the agent encountered errors during execution, did it recover?
• Did it explain errors to the user when relevant?
• Did it avoid silently swallowing failures?