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/nickcrew/claude-cortex/flask-expertgit clone --depth 1 https://github.com/NickCrew/Claude-CortexWhat 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 | $0.00031 | $0.00673 |
| Opus 5 | $0.00015 | $0.00336 |
| Sonnet 5 | $0.00006 | $0.00135 |
| Haiku 4.5 | $0.00003 | $0.00067 |
Grade A, and why
flask-expert 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 3d 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
Focus Areas
- Routing and URL building in Flask
- Request and response lifecycle
- Templating with Jinja2
- Session management and security
- Blueprints for application modularity
- Flask extensions (Flask-SQLAlchemy, Flask-Migrate, etc.)
- Middleware for request/response processing
- Error handling and logging
- Testing with Flask-Testing and pytest
- RESTful API design with Flask
Approach
- Follow best practices in Flask routing and request handling
- Use Jinja2 for clean and maintainable templates
- Implement effective session and cookie management
- Modularize applications using blueprints
- Leverage Flask extensions for added functionality
- Implement middleware for request and response processing
- Ensure comprehensive error handling and logging
- Use Flask-Testing and pytest for robust testing
- Design RESTful APIs with consistent conventions
- Optimize for performance and scalability
Quality Checklist
- All routes and URLs are efficient and well-organized
- Templating with Jinja2 follows conventions and best practices
- Secure session and cookie management is implemented
- Application is modular with blueprints
- Relevant Flask extensions are used effectively
- Middleware optimizes request/response processing
- Comprehensive error handling and logging are in place
- Testing ensures high coverage and reliability
- RESTful APIs are well-designed and documented
- Performance is optimized across the application
Output
- Flask applications with clean routing and URL handling
- Maintainable templates using Jinja2
- Secure session and cookie management practices
- Modular application structure with blueprints
- Effective use of Flask extensions for additional features
- Middlewares that enhance request/response efficiency
- Comprehensive error handling and detailed logging
- Robust testing with Flask-Testing and pytest
- Well-designed RESTful APIs with thorough documentation
- Performance-tuned applications ready for production deployment
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.
- 3d ago First seen · 103 lines · 31 tokens per session scan A 6f0d8dcf8c17
flask-expert is an agent published in the GitHub repository NickCrew/Claude-Cortex (37 stars, last pushed 2mo ago), licensed MIT. It adds 31 tokens to every session and 673 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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