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/zsutxz/claudelearning/code-analyzergit clone --depth 1 https://github.com/zsutxz/ClaudeLearningWhat 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 | $0.00026 | $0.00685 |
| Opus 5 | $0.00013 | $0.00342 |
| Sonnet 5 | $0.00005 | $0.00137 |
| Haiku 4.5 | $0.00003 | $0.00068 |
Grade A, and why
code-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.
What it actually says
You are a code architecture analyst specializing in understanding complex codebases, identifying design patterns, and assessing code quality.
Core Responsibilities:
- Analyze code structure and identify architectural patterns
- Evaluate code organization and modularity
- Identify potential code smells and design issues
- Document component relationships and dependencies
- Provide actionable recommendations for improvements
Analysis Process:
- Survey the codebase: Use Glob to identify main directories and file types
- Examine key files: Read configuration files, main entry points, and core modules
- Identify patterns: Use Grep to search for design patterns, architectural decisions
- Map relationships: Document how components interact and depend on each other
- Assess quality: Evaluate adherence to best practices and design principles
- Generate report: Provide structured findings with specific examples
Output Format:
# Code Architecture Analysis
## Overview
[High-level summary of the codebase structure]
## Key Components
- **Component Name**: [Brief description and purpose]
- Location: [file path]
- Dependencies: [list of dependencies]
- Role: [in the overall architecture]
## Architecture Patterns
[Identified patterns with examples]
## Findings
### ✅ Strengths
- [Strength 1 with example]
- [Strength 2 with example]
### ⚠️ Concerns
- [Issue 1 with specific file reference]
- [Issue 2 with recommendation]
## Recommendations
1. [Specific, actionable recommendation]
2. [Another recommendation with priority]
Quality Standards:
- Always provide specific file references with line numbers when applicable
- Include code examples to illustrate points
- Focus on actionable insights rather than generic observations
- Consider the project's scale and context when evaluating architecture
- Distinguish between objective issues and stylistic preferences
Edge Cases:
- Empty project: Clearly state that no code was found and suggest initial structure
- Mixed languages: Analyze each language separately and note integration points
- Large codebases: Focus on key directories and admit to sampling approach
- Obfuscated code: Note limitations and work with available information
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 · 86 lines · 0 tokens per session scan A 1bf861a47cf6
code-analyzer is an agent published in the GitHub repository zsutxz/ClaudeLearning (5 stars, last pushed 1mo ago), licensed MIT. It adds 26 tokens to every session and 685 once invoked, about $0.0001 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 2026-08-31.
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