Skill UI

A comprehensive guide detailing how to configure and manage GitHub's secret scanning feature. This skill covers enabling Secret Protection, setting up push protection to block leaked credentials before they reach the repository, defining custom regex patterns, and providing workflows for triaging alerts and resolving blocked pushes (including using git rebase or bypassing protections). Essential for maintaining secure code repositories and complying with security standards.

A comprehensive tool that analyzes existing codebases to generate detailed, definitive architectural blueprints. It automatically detects technology stacks, identifies architectural patterns (e.g., Microservices, Clean Architecture), and documents implementation details, including dependency flow, cross-cutting concerns (security, logging), and data models. This ensures architectural consistency, aids in onboarding new team members, and guides future development efforts.

Checks AI agent implementations against the OWASP Agentic Security Initiative Top 10 risks, producing findings on controls, vulnerabilities, and recommendations for prompt injection, tool governance, escalation, logging, identity, policy, supply chain, and behavioral monitoring before production or audit.

Conducts comprehensive AI prompt safety reviews that analyze bias, misinformation, injection, and privacy risks while delivering effectiveness evaluations, security guidance, and best-practice recommendations for prompt engineers.

Explains Fabric Lakehouse storage, data organization, security, shortcuts, and optimization practices so you can design, build, and monitor Lakehouse solutions leveraging Microsoft Fabric best practices.

A universal assistant for conducting deep code reviews across major SQL databases (MySQL, PostgreSQL, SQL Server, Oracle). It rigorously analyzes SQL code for critical vulnerabilities (like SQL injection), performance bottlenecks, maintainability issues, and adherence to industry best practices. Features include security audits, index optimization recommendations, query structure analysis, and schema design validation, ensuring robust and secure database development.

A comprehensive, five-stage methodology for reviewing code quality. This process systematically checks for requirements compliance, logical correctness, code maintainability, test coverage, and critical security/performance vulnerabilities. It provides actionable feedback categorized by severity (Blocker, Major, Minor, Nit), ensuring high standards for all merged code.

This guide details Algolia's security best practices, focusing on scoped API keys. It covers essential concepts like separating API keys for frontend vs. backend use, applying the principle of least privilege, and generating secured, time-limited, per-user keys. It also provides a complete procedure for key rotation to maintain a robust production security posture.

Provides comprehensive security guidelines for integrating Anthropic Claude API. Covers essential best practices including secure API key management (rotation, isolation), defending against prompt injection attacks by separating system instructions from user input, robust input sanitization, and output validation to prevent accidental data leakage. Essential for building production-grade, secure AI applications.

This guide provides essential security controls for integrating with the Attio REST API. It details best practices for managing API tokens, including applying least-privilege scopes, implementing secure secret management across various platforms (AWS, Vercel, etc.), executing proper token rotation, and validating webhook signatures to prevent common security vulnerabilities.

This guide details essential security best practices for integrating with the Canva Connect API. It covers securing OAuth 2.0 tokens, implementing least-privilege scopes, ensuring secure token storage (encryption and server-side handling), and verifying webhook signatures using JWK. Essential for building robust and secure Canva integrations.

This guide details securing the CAST AI integration across multiple layers. It covers best practices for API key management (including rotation and secrets storage), implementing least-privilege RBAC using 'kubectl', deploying the Kvisor security agent for runtime scanning, and setting up Kubernetes Network Policies to restrict egress traffic. Use this when hardening production clusters or performing security audits.