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.
git clone --depth 1 https://github.com/NickCrew/Claude-CortexWrote 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/nickcrew/claude-cortex/flask-expert)<a href="https://agentmods.dev/agents/nickcrew/claude-cortex/flask-expert"><img src="https://agentmods.dev/badge/agents/nickcrew/claude-cortex/flask-expert/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/nickcrew/claude-cortex/flask-expert"><img src="https://agentmods.dev/badge/agents/nickcrew/claude-cortex/flask-expert.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 | $0.00031 | $0.00673 |
| Opus 5.5 | $0.00012 | $0.00269 |
| Sonnet 5.5 | $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 1mo 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.
- 1mo 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 (56 stars, last pushed 3mo ago), licensed MIT. It adds 31 tokens to every session and 673 once invoked, about $0.0001 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 2026-08-30.
Other agents, from other repositories
nextjs-expert
Expert Next.js developer specializing in App Router, React Server Components, and full-stack patterns. Comprehensive knowledge of Next.js 15+, Turbopack, server/client component architecture, streaming, performance optimization, testing, and production deployment. Use for any Next.js development needs including setup…
fastapi-architect
Expert in building production FastAPI applications with modern Python patterns. Specializes in Pydantic v2 models, SQLAlchemy 2.0 async patterns, JWT auth, and API architecture.
api-development-agent
Design and build professional APIs with REST, GraphQL, and gRPC. Master authentication (JWT, OAuth2), API documentation (OpenAPI), testing strategies, versioning, rate limiting, and real-time communication patterns.
testing-security-agent
Comprehensive testing strategies (unit, integration, E2E, contract, load), security best practices (OWASP Top 10), vulnerability scanning (SAST, DAST, SCA), compliance frameworks (GDPR, HIPAA, PCI-DSS), and production monitoring with observability.
gcp-cloud-architect
GCP cloud architect specializing in designing and implementing scalable Google Cloud solutions. Expert in GCE, GKE, Cloud Run, App Engine, and GCP best practices for containerized and serverless deployments.
swe-api-tester
Judges a running request-based interface with real requests under one charter, against its contract and behaviour specifications, and records criticality-rated findings with reproducing requests without fixing anything.