# General Quality

> General response quality evaluation. Always applicable regardless of domain. Covers response structure, actionability, clarity, and hallucination detection.

- Skill: `databricks-solutions/general-quality` (Agent Skill)
- Install (CLI): `npx skillmds@latest add databricks-solutions/general-quality`
- Raw SKILL.md: https://api.skillmd.com/api/skills/databricks-solutions/general-quality/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: databricks-solutions (https://skillmd.com/u/databricks-solutions)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/databricks-solutions/general-quality

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## 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?