Skill UI

Automates Accelo operations via Composio's Rube MCP, guiding discovery of tool schemas, connection checks, and multi-execution workflows for reliable task automation across Accelo tasks.

Automates Affinity tasks through Composio’s toolkit by using the Rube MCP commands to search for current tool schemas, validate the affinity connection, and execute schema-compliant workflows across RUBE_SEARCH_TOOLS, RUBE_MANAGE_CONNECTIONS, and RUBE_MULTI_EXECUTE_TOOL.

Automatically detects and loads specialized agent instructions from the `AGENTS.md` file in the current working directory. This skill seamlessly integrates project-specific rules and behavioral guidelines into the AI's session context, ensuring the AI operates according to project standards without manual intervention. It is crucial for maintaining specialized agent behaviors across different development tasks and directory changes.

This skill defines structured behavioral frameworks (e.g., Brainstorm, Implement, Debug, Review, Teach, Ship) to guide the AI's output and approach based on the specific task phase. It optimizes performance by ensuring the AI adopts the correct mindset and output format—from initial ideation to final deployment—guaranteeing systematic, high-quality results across the entire development lifecycle.

Automate ClickUp project management workflows across tasks, hierarchies, and comments via Rube MCP/Composio. Always fetch current tool schemas before managing connections and executing task or list operations.

Automates guidance for setting up Cloud Tasks queues across GCP workloads, covering patterns, best practices, and vetted configs.

Addresses the critical challenge of managing extremely long conversation histories (millions of tokens) in advanced AI agents, such as coding assistants. This technique moves beyond simple token minimization by implementing structured compression strategies (like Anchored Iterative Summarization) to prevent the loss of critical technical details—such as file paths, decisions, and error messages—ensuring the agent maintains functional context across complex, multi-step tasks. It emphasizes optimizing for 'tokens-per-task' rather than just tokens-per-request.

This tool optimizes the codebase indexing within Cursor. It processes your entire codebase, converting code chunks into vector embeddings stored in a vector database. This enables advanced @Codebase semantic search, allowing users to ask natural language questions (e.g., "Where is authentication handled?") and retrieve the most relevant code snippets, significantly improving AI context awareness across chat and coding tasks.

A powerful AI tool designed for complex, coordinated programming tasks. It enables developers to generate, refactor, and scaffold entire features across multiple files (e.g., schema, API routes, service layers, tests) while maintaining consistency with existing codebase patterns. It supports agent mode for autonomous, multi-step changes and allows systematic migration and review of all affected files via detailed diffs.

Guides AWS users through validating, generating, and following best practices for EKS cluster configuration tasks across compute, storage, networking, and serverless environments.

Automates guidance for API filtering query builder tasks, offering industry best practices, production-ready code, and validation across REST, GraphQL, OpenAPI, and authentication design patterns.

Automated DevOps helper for Git workflow manager tasks, triggering on mentions to offer best practices, code and configuration generation, and validation across version control, containerization, CI/CD, and foundational infrastructure topics.