Skill UI

Guides chaos engineering experiments by defining objectives, choosing tools such as Chaos Mesh, Gremlin, Toxiproxy, or AWS FIS, injecting failures, monitoring metrics, and recommending fixes to harden services and APIs.

This skill validates the completeness, consistency, and correctness of Conductor project artifacts. It checks for the existence of required directories, verifies essential project documentation (like index.md, product.md, etc.), and confirms adherence to established naming and status patterns. Use this tool after setup, when diagnosing issues, or before implementation to ensure the project context is sound.

Handles Confluence page search, creation, updates, space listings, and comments through Atlassian MCP tools; enforces Markdown bodies, natural-language Rovo Search, and Cloud ID/URL detection before any operation.

Automates Confluence page creation, updates, searches, space management, labels, and hierarchy navigation through Rube MCP (Composio), enabling teams to script documentation workflows, honor workspace schemas from RUBE_SEARCH_TOOLS, and keep content consistent.

Automates connection pool analyzer tasks for performance testing, offering best-practice guidance, code/config generation, and validation during load, stress, and benchmarking activities.

Automates guidance for configuring connection pooling during API integrations, offering best practices, validated code/config templates, and step-by-step help so pooling setups resolve quickly.

Automate Contentful headless CMS space operations from Claude Code, listing spaces, fetching metadata, and renaming spaces via the Composio Contentful toolkit without leaving your terminal.

Automates Contentful GraphQL workflows via the Composio Rube MCP toolkit by first querying RUBE_SEARCH_TOOLS for current schemas, verifying contentful_graphql connections, and executing schema-compliant tool calls with RUBE_MULTI_EXECUTE_TOOL while handling sessions, pagination, and memory.

This advanced system transforms session interactions into reusable, atomic knowledge units called "Instincts." By hooking into tool usage and session activity, it observes patterns (like preferred coding styles, error fixes, or repeated workflows). These instincts are then clustered and "evolved" into structured Skills, Commands, or specialized Agents, capturing deep contextual knowledge with weighted confidence scoring to enhance development productivity.

Automates Conversion Tools workflows by orchestrating Composio’s toolkit through Rube MCP, guiding users to discover current schemas, verify connections, and execute schema-compliant tool calls with memory/session handling.

Guides using Rube MCP via Composio to discover Convertapi tool schemas, manage toolkit connections, and execute safe multi-step conversions without hardcoded slugs.

Automate Conveyor tasks through Composio's Rube MCP pipeline by discovering current tool schemas first, ensuring active connections, and executing schema-compliant workflows for reliable operations.