Skill UI

This comprehensive guide provides minimal working examples for key Adobe APIs: Firefly AI image generation, PDF content extraction, and Photoshop background removal. It serves as a practical quickstart for developers starting new Adobe integrations, testing API connectivity, or learning basic API calling patterns using TypeScript and Node.js.

This guide assists developers in upgrading the Anima SDK versions and managing associated API changes. It covers migrating from manual Figma plugin workflows to automated SDK-based code generation, ensuring seamless integration of the latest design system features into development projects.

A comprehensive guide for developers on upgrading the Anthropic SDK versions and migrating between different Claude model generations. It covers best practices for version checking, reviewing breaking changes, updating model IDs across the codebase, running output comparison tests, and implementing gradual rollouts using environment variables to ensure stable deployment.

A comprehensive setup for creating a fast and reproducible local development loop for building Attio REST API integrations. This guide includes project structure setup, typed client generation, a mock server implementation (using MSW) for offline development, and a full test harness for unit and integration testing. Ideal for developers building complex SaaS integrations.

This skill automatically converts structured data specifications (such as CSV, JSON schemas, SQL DDL, or Protobuf definitions) into functional, production-ready code. It generates complete models, validation logic, full CRUD API endpoints, and unit tests in multiple languages (Python, TypeScript, Go, etc.), significantly reducing boilerplate coding time and ensuring type safety.

This skill automates the validation of Navan API integrations within CI/CD pipelines. It generates robust GitHub Actions workflows to perform comprehensive tests, including token health checks, booking data schema validation, and automated compliance report generation. By integrating these checks into your push/pull request process, it ensures the stability and adherence of your Navan connection without requiring a dedicated SDK.

This is a detailed offensive checklist for identifying and exploiting insecure deserialization vulnerabilities across multiple programming languages (Java, Python, PHP, .NET, Node.js, etc.). It covers techniques like gadget chain generation, magic method abuse, type confusion, and modern attack vectors, providing a deep methodology for penetration testing and vulnerability research.

This skill provides a comprehensive checklist and methodology for identifying Server-Side Template Injection (SSTI) vulnerabilities. It covers template engine identification (e.g., Jinja2, Twig), polyglot payload generation, systematic detection methods, and executing engine-specific Remote Code Execution (RCE) payloads. Ideal for security professionals testing web application input sanitization.

This skill synthesizes a comprehensive Product Requirements Document (PRD) from the current conversation context and understanding of the codebase. It guides the user through structuring the problem statement, defining detailed user stories, outlining implementation decisions, and suggesting test strategies. The final PRD is formatted and submitted directly as a GitHub issue, ensuring a structured handover from discussion to development specification.

This guide provides a comprehensive tutorial on running various AI inference tasks using the Together AI API, which is compatible with the OpenAI standard. It demonstrates key functionalities including chat completions, streaming responses, image generation, and creating embeddings. This is ideal for developers who need to test open-source models, compare performance across different LLMs (like Llama or Mixtral), or integrate powerful generative AI features into their applications using Python or Node.js.

This tool provides a comprehensive security assessment framework for Retrieval-Augmented Generation (RAG) systems and vector databases. It tests critical vulnerabilities such as embedding inversion, cross-tenant data leakage, knowledge-base poisoning, and retrieval manipulation, aligning with OWASP LLM08:2025 standards. It is essential for validating the security posture of multi-tenant and vector-search applications.

This skill guides the deployment and operation of the Havoc C2 framework, enabling advanced adversary emulation. It utilizes Yaotl profiles to generate highly evasive agents (Demon) that employ sophisticated techniques like indirect syscalls and sleep obfuscation. The scope covers the full red-teaming lifecycle, including C2 setup, payload generation, post-exploitation, and lateral movement, making it ideal for authorized security testing and validating EDR detection capabilities.