Skill UI

Deploys and orchestrates Vertex AI ADK agents via the A2A protocol, covering AgentCard discovery, sandboxed code execution, memory banks, orchestration patterns, and Vertex AI Agent Engine rollout for CI/CD-style automation.

A comprehensive toolkit for designing, architecting, and evaluating complex multi-agent systems. It provides structured patterns—including Supervisor, Swarm, and Pipeline—for system architecture, defines agent roles (Coordinator, Specialist), and covers best practices for communication (Event Sourcing, Message Passing), tool design, and safety guardrails, ensuring robust and scalable AI workflows.

Automate Astica AI workflows through Composio’s Rube MCP bridge by discovering tools with RUBE_SEARCH_TOOLS, managing Astica connections, and executing tasks via RUBE_MULTI_EXECUTE_TOOL while respecting dynamic schemas.

Automates Castingwords tasks through Composio’s Rube MCP workflow: discover tooling via RUBE_SEARCH_TOOLS, ensure an active Castingwords connection, then execute schema-compliant operations and bulk jobs while respecting pagination and session reuse.

Provides elite guidance on dynamic context management, vector databases, knowledge graphs, intelligent memory, RAG, and multi-agent workflows so AI systems maintain relevant, actionable information across enterprise scenarios.

A specialized skill for optimizing LLM applications handling long conversations and large datasets. This guide teaches advanced context engineering techniques, addressing issues like context rot, token limits, and the lost-in-the-middle problem. Capabilities include intelligent summarization, context trimming, information prioritization, and strategic context routing to ensure critical information is retained and utilized effectively throughout the dialogue.

A framework for designing and orchestrating collaborative AI agent teams. It allows users to define specialized agent personas, assign clear roles and responsibilities, and structure complex workflows through defined tasks. Supports sequential, hierarchical, and planning process types, making it ideal for complex, multi-step automation tasks.

Cursor AI Debug Toolkit helps identify root causes of incorrect Cursor AI suggestions, inspect completion/chat context, and use dev tools/logs to tweak settings, re-test models, and document fixes for future issues.

Configure project-specific `.cursorrules` files to guide Cursor IDE’s AI code generation, enforce style, and supply contextual metadata for consistent suggestions.

Implements Exa-specific policy guardrails covering domain allow/block lists, content filtering, freshness checks, and API usage quotas to keep neural search results safe and compliant when integrating Exa into CI/production flows.

FAISS (Facebook AI Similarity Search) is a library designed for efficient similarity search and clustering of dense vectors. It supports indexing and searching on billions of vectors at scale, featuring GPU acceleration and multiple index types (Flat, IVF, HNSW, PQ) to balance speed and accuracy. It is essential for building high-performance, large-scale applications requiring fast k-NN retrieval or pure vector similarity matching, especially in fields like RAG and recommendation systems.

Ensures Gamma integrations respect privacy by implementing consent gates, PII sanitization, retention schedules, GDPR request handling, and audit trails so teams can deploy compliant workflows.