Skill UI

A comprehensive utility designed to collect all necessary diagnostic evidence for troubleshooting Ideogram API interactions. It gathers environment details (Node, Python, OS), performs API connectivity tests, captures network information, and packages the results into a redacted tarball suitable for attaching to technical support tickets, ensuring all sensitive data is masked.

This guide provides a comprehensive technical deep dive for developers migrating image generation workflows from services like DALL-E, Midjourney, and Stable Diffusion to Ideogram. It covers API parameter mapping, architectural patterns (like the Adapter pattern), and provides code examples to ensure a stable, gradual, and feature-rich transition to Ideogram's platform.

This guide outlines the process of migrating codebase dependencies and logic when upgrading the Ideogram API from legacy versions (V1/V2) to the robust V3 endpoints. It addresses critical breaking changes, including the shift from JSON body to multipart/form-data, changes in model naming, aspect ratio syntax, and the integration of new V3 features like rendering speed and style presets. Provides structured code adapters for smooth transition.

Automates Jigsawstack operations through Composio via the Rube MCP adapter, guiding users to discover current tool schemas, verify connections, and execute schema-compliant tasks safely.

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 utility designed to gather all necessary diagnostic evidence for troubleshooting complex LangChain failures. It captures environment snapshots, dependency versions, detailed execution traces (including LLM calls and tool usage), and error stack traces. Use this bundle when preparing detailed GitHub bug reports or conducting LangSmith tracing.

Master the configuration of Langfuse webhooks to capture crucial prompt lifecycle events (Created, Updated, Deleted). This skill guides you through building a secure endpoint to intercept these events, enabling powerful, automated integrations. Use cases include triggering CI/CD pipelines upon production prompt changes, syncing data to external systems, or notifying teams via Slack.

Implement robust, structured logging for API requests, capturing performance metrics, correlation IDs, and detailed security audit trails. This skill ensures compliance by handling PII redaction and providing comprehensive, JSON-formatted logs suitable for ELK Stack or Loki. Essential for debugging, performance analysis, and maintaining SOC 2 compliance in distributed microservices.

This specialized skill provides a comprehensive framework for migrating applications using the MaintainX API across different versions (e.g., v1 to v2). It covers best practices for handling API breaking changes, deprecations, and version compatibility. Users can audit existing API usage, implement version adapters, and manage feature flag rollouts, ensuring smooth and safe integration upgrades.

A comprehensive guide to implementing event-driven integrations with MaintainX. This skill covers setting up webhooks to capture real-time updates for work orders, asset changes, and maintenance notifications. It includes best practices like HMAC signature verification, idempotent processing to prevent duplicate actions, and setting up local development environments.

A comprehensive guide for migrating existing AI integrations from providers like OpenAI or Anthropic to Mistral AI. This blueprint covers the entire lifecycle: initial assessment of AI touchpoints, detailed model mapping (e.g., gpt-4o to mistral-large), implementing a provider-agnostic adapter pattern, and executing controlled, feature-flag-controlled rollout plans for major refactoring projects.

This bundle collects comprehensive diagnostic evidence from the OpenEvidence clinical decision support API. It validates API credentials, checks query endpoint health, retrieves evidence citations, and captures model metadata. Use it to diagnose complex issues like query failures, missing references, or high latency without needing direct dashboard access.