Skill UI

Guides teams through AI SEO practices that make content discoverable and citable by assistants like ChatGPT, Gemini, Perplexity, and Google AI Overviews, including visibility audits, extractability checks, and bot access review.

Use Composio’s Botpress toolkit through Rube MCP to orchestrate Botpress workflows: always search tools for the latest schemas, confirm the Botpress connection, then execute discovered operations via RUBE_MULTI_EXECUTE_TOOL with schema-compliant inputs.

Automate Browserhub workflows through Composio’s Rube MCP toolkit by discovering tools with RUBE_SEARCH_TOOLS, verifying Browserhub connections, and executing schema-approved actions via RUBE_MULTI_EXECUTE_TOOL.

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.

Automate Chatfai operations through the Rube MCP connector by always discovering tool schemas, validating the chatfai connection, and invoking RUBE_MULTI_EXECUTE_TOOL with schema-compliant arguments and memory placeholders.

Guides researchers through ten structured ideation frameworks to move from vague curiosity to actionable, defensible research proposals, supporting exploration of new problem spaces, pivoting projects, and surfacing high-impact angles.

Chroma is an open-source, AI-native embedding database designed for building sophisticated LLM applications. It allows users to store high-dimensional embeddings and associated metadata, facilitating powerful vector search and full-text filtering. Ideal for implementing Retrieval-Augmented Generation (RAG) systems, semantic search, and document retrieval in local or self-hosted environments, making it perfect for open-source AI projects and prototyping.

CLIP enables general-purpose vision-language tasks through zero-shot image classification, similarity scoring, semantic search, and content moderation using pretrained contrastive embeddings without fine-tuning.

A sophisticated system for recovering and reconstructing complex project context across distributed, multi-agent AI workflows. It utilizes advanced semantic vector search, relevance filtering, and optimized rehydration patterns to maintain high knowledge fidelity and ensure seamless continuity in long-running, complex AI projects. Essential for advanced RAG implementations.

A sophisticated memory management system designed to recover, reconstruct, and maintain project context across complex, distributed, and multi-agent AI workflows. It specializes in advanced semantic memory rehydration, utilizing semantic vector search, relevance ranking, and conflict resolution to ensure seamless continuity and high fidelity of historical knowledge.

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.

Automate Datarobot operations via Composio's Rube MCP by discovering tool schemas, managing connections, and executing workflows with RUBE_MULTI_EXECUTE_TOOL while observing schema compliance and session reuse best practices.