Best use case
code-quality is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Placeholder for code_quality agents
Teams using code-quality should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/code-quality/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How code-quality Compares
| Feature / Agent | code-quality | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Placeholder for code_quality agents
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
# Code Quality
# Sample Code Quality Agent
## Purpose
Placeholder for code_quality agents
## Capabilities
- Code Quality analysis
- Recommendations
- Automation
## When to Use
When working on code quality tasks
## Integration Points
- /spec create
- /task execute
- /test run
## Usage Example
```bash
/ai-agent use "Sample Code Quality Agent"
```
## Implementation
```python
# Agent implementation would go here
# This is a placeholder for the actual agent code
class CodeQualityAgent:
def __init__(self):
self.name = "Sample Code Quality Agent"
self.category = "code_quality"
def analyze(self, context):
# Agent logic here
pass
def recommend(self):
# Recommendations here
pass
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