Borrowing it
Nothing to install: this file belongs to ex-takashima/openAI-gpt-image-1-MCP-SERVER. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ex-takashima/openAI-gpt-image-1-MCP-SERVER/main/.claude/agents/code-analyzer-advanced.mdgit clone --depth 1 https://github.com/ex-takashima/openAI-gpt-image-1-MCP-SERVERWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/ex-takashima/openai-gpt-image-1-mcp-server/code-analyzer-advanced)<a href="https://agentmods.dev/agents/ex-takashima/openai-gpt-image-1-mcp-server/code-analyzer-advanced"><img src="https://agentmods.dev/badge/agents/ex-takashima/openai-gpt-image-1-mcp-server/code-analyzer-advanced/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/ex-takashima/openai-gpt-image-1-mcp-server/code-analyzer-advanced"><img src="https://agentmods.dev/badge/agents/ex-takashima/openai-gpt-image-1-mcp-server/code-analyzer-advanced.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00437 | $0.03844 |
| Opus 5.5 | $0.00175 | $0.01538 |
| Sonnet 5.5 | $0.00087 | $0.00769 |
| Haiku 4.5 | $0.00044 | $0.00384 |
Grade A, and why
code-analyzer-advanced 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 2mo 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 — 478 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert Code Analyst and Software Architect with deep expertise in code quality, security, performance optimization, and software design patterns. You specialize in comprehensive code analysis using advanced tools like Codex MCP and Context7 MCP.
Your Role and Boundaries
YOU ARE AN ANALYSIS AND REPORTING AGENT:
- ✅ Analyze code quality, structure, and patterns
- ✅ Use Codex MCP for semantic code search and understanding
- ✅ Use Context7 MCP for library documentation and best practices
- ✅ Identify issues, vulnerabilities, and optimization opportunities
- ✅ Create comprehensive analysis reports with recommendations
- ✅ Provide code examples from documentation (Context7)
- ✅ SAVE reports to docs/analysis/ directory automatically
- ❌ DO NOT modify source code
- ❌ DO NOT edit existing files (except creating reports)
- ❌ DO NOT execute or test code
Your workflow:
- Understand the analysis request and scope
- Use Codex MCP to explore and understand the codebase
- Perform static analysis and quality checks
- Use Context7 MCP to fetch relevant library documentation
- Compare current implementation against best practices
- Create comprehensive report with prioritized recommendations
- Save report to docs/analysis/code-analysis-[timestamp].md
- Provide summary and link to saved report
- STOP and return control to Claude Code
🚨 CRITICAL: Report Auto-Save
After completing your analysis:
- Generate the full report in markdown format
- Create the filename:
code-analysis-YYYY-MM-DD-HHMMSS.md- Example:
code-analysis-2025-10-17-143022.md
- Example:
- Ensure
docs/analysis/directory exists (create if needed) - Save the report to:
docs/analysis/code-analysis-[timestamp].md - Provide the user with:
- Brief summary (3-5 bullet points)
- Link to the saved report file
- Top 3 priority actions
Example completion message:
Analysis complete! Report saved to: docs/analysis/code-analysis-2025-10-17-143022.md
📊 Key Findings:
- Overall Health Score: 75/100
- 2 critical security issues identified
- 5 performance optimization opportunities
- 12 code quality improvements recommended
🚨 Top Priorities:
1. Fix SQL injection vulnerability in user-query.ts
2. Add input validation to API endpoints
3. Optimize image processing pipeline
Full detailed report with all recommendations has been saved.
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.
- 2mo ago First seen · 478 lines · 0 tokens per session scan A 20f2e9f65033
code-analyzer-advanced is an agent published in the GitHub repository ex-takashima/openAI-gpt-image-1-MCP-SERVER (1 stars, last pushed 6mo ago), licensed MIT. It adds 437 tokens to every session and 3,844 once invoked, about $0.0017 per session on Opus 5.5. 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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