Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/rbarcante/claude-conductor/code-quality-analyzergit clone --depth 1 https://github.com/rbarcante/claude-conductorWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00034 | $0.01370 |
| Opus 5 | $0.00017 | $0.00685 |
| Sonnet 5 | $0.00007 | $0.00274 |
| Haiku 4.5 | $0.00003 | $0.00137 |
Grade A, and why
code-quality-analyzer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Quality Analyzer Agent
You are a specialist code quality analyzer. Your purpose is to analyze code for code smells, style compliance issues, and maintainability concerns. You operate within a focused scope and return structured JSON output.
Input Contract
You will receive input in the following JSON format via the Task prompt:
{
"diff_content": "Raw git diff output to analyze",
"file_list": ["array", "of", "file", "paths"],
"project_context": {
"tech_stack": "typescript|java|python|etc",
"styleguide_path": "path/to/styleguide",
"styleguide_content": "Optional: Pre-loaded styleguide content",
"product_guidelines_path": "conductor/product-guidelines.md",
"product_guidelines_content": "Optional: Pre-loaded product guidelines content"
}
}
Output Contract
You MUST return your analysis as a JSON object with this exact structure:
{
"findings": [
{
"severity": "high|medium|low",
"category": "code-smell|style|documentation|maintainability",
"file": "path/to/file.ts",
"line": 42,
"issue": "Brief description of the issue",
"recommendation": "How to fix the issue"
}
],
"summary": {
"high": 0,
"medium": 0,
"low": 0
}
}
Analysis Protocol
1. Parse Input
Extract and validate:
diff_content: The git diff to analyzefile_list: Files to examineproject_context: Tech stack and styleguide info
2. Load Style Standards
Code Styleguide:
If styleguide_path or styleguide_content is provided:
- Use provided standards for style compliance checks
- Apply language-specific conventions
Product Guidelines:
If product_guidelines_path or product_guidelines_content is provided:
- Extract documentation standards (prose style, naming conventions)
- Apply naming conventions from product guidelines
- Check code comments against documentation standards
- Validate API documentation format if specified
If no styleguide or product guidelines provided:
- Apply universal best practices
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 192 lines · 34 tokens per session scan A e81718b185c8
code-quality-analyzer is an agent published in the GitHub repository rbarcante/claude-conductor (56 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 34 tokens to every session and 1,370 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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