Skill UI

Automate Keap CRM tasks through Composio’s Rube MCP toolkit, ensuring that tools are discovered, connections verified, and schema-compliant executions run before each workflow.

Guides operators how to automate Kickbox tasks using Composio’s Rube MCP interface, emphasizing always discovering current schemas via RUBE_SEARCH_TOOLS, confirming Kickbox connections, and invoking multi-tool execution with schema-compliant arguments plus session/memory handling.

Guides you through automating Composio Kit tasks via the Rube MCP workflow, emphasizing schema discovery, connection checks, and schema-compliant executions before running multi-tool operations.

Automate Klaviyo email and SMS campaign tasks through Rube MCP via Composio, covering campaign discovery, message inspection, tag management, and send-job monitoring with guided tool sequences and pagination advice.

This skill provides a comprehensive pattern for building robust, scalable, and fault-tolerant asynchronous video generation pipelines using Kling AI. It implements advanced software engineering patterns, including Redis queues (Producer/Consumer), State Machines, and event-driven callbacks. It is designed for managing complex, multi-step AI workflows—such as generate, extend, and download—ensuring reliable background task processing.

This module provides a compliance-grade, tamper-evident logging solution for tracking all Kling AI operations. It records task submissions, status changes, and credential usage into structured, hashed logs. Use this when meeting regulatory compliance requirements or preparing for internal/external security audits.

This guide provides a comprehensive reference for diagnosing and resolving common errors encountered when interacting with the Kling AI API. It covers various HTTP status codes (e.g., 400, 401, 429), task-level failures (e.g., content policy violations, low image quality), proper JWT token management, and implementing rate limit handling with exponential backoff. Use this resource when troubleshooting failed video generation or API integration issues.

A comprehensive framework for assessing the security, privacy, and compliance posture of Kling AI integrations. It covers crucial areas such as data residency, credential management, content policy adherence, and GDPR compliance (e.g., right to erasure). Use this guide when preparing for security audits or implementing robust data handling protocols for AI-generated content.

Implements robust content policy compliance for generative AI prompts and outputs, such as those from Kling AI. This skill provides pre-submission filtering functionality, preventing the generation of restricted content (e.g., violence, explicit material, hate speech) and saving API credits. It includes Python code examples for prompt screening and handling server-side rejection messages.

A comprehensive utility for structured logging, request tracing, and diagnostic purposes when integrating with the Kling AI API. It automatically captures request/response pairs, task lifecycle events, and detailed timing metrics for every API call, making troubleshooting video generation pipelines efficient and systematic. Ideal for developers building robust, observable AI applications.

A comprehensive guide detailing how to set up secure API authentication for Kling AI using JSON Web Tokens (JWT). This process involves generating tokens from your Access Key (AK) and Secret Key (SK) credentials, providing code examples for Python and Node.js, and implementing best practices for token management and refreshing to ensure continuous API access.

This skill provides comprehensive monitoring and tracking for asynchronous video generation tasks using the Kling AI API. It supports polling single tasks, managing large batches of jobs, and detecting stalled or failed processes across multiple video endpoints. Ideal for developers building robust workflow dashboards, implementing reliable batch processing, or debugging long-running media generation pipelines.