Skill UI

A specialized skill designed to assist in drafting professional and structured internal communications. It provides guidelines and formats for various corporate documents, including 3P updates (Progress, Plans, Problems), company newsletters, status reports, FAQ responses, and incident reports. Use this skill to ensure consistency in tone and structure across all internal messaging.

A comprehensive runbook detailing incident response procedures for failures within the Juicebox AI platform. It guides technical users through diagnosing and resolving critical issues such as API outages, data corruption, quota exhaustion, and export failures, ensuring minimal downtime for recruiting and talent intelligence workflows.

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 production-ready Python SDK providing comprehensive patterns for integrating with the Kling AI API. This wrapper handles crucial operational complexities such as auto-refreshing JWT tokens, structured request/response models, exponential backoff polling for long-running tasks, and detailed error handling. Use this library when building stable, high-reliability applications that require advanced text-to-video or image-to-video synthesis capabilities.

Implement comprehensive end-to-end tracing for Large Language Model (LLM) calls, chains, and complex agents using Langfuse. This workflow demonstrates techniques like OpenAI drop-in wrappers, manual span creation for RAG pipelines, tracking streamed responses, and integrating with various LLM providers (OpenAI, Anthropic). Use this to monitor latency, track token usage, and debug complex AI features in production.

A comprehensive guide for troubleshooting and resolving Langfuse-related incidents and outages. It provides step-by-step procedures for initial triage, severity assessment, implementing fallback modes, and resolving common issues like missing traces or rate limits, ensuring continuous observability monitoring for LLM applications.

A comprehensive runbook detailing procedures for responding to failures and outages across Lindy AI agents. Covers critical scenarios including platform downtime (SEV1), individual agent failures, integration authentication issues, credit exhaustion, and webhook endpoint failures. Provides structured diagnostics and fallback strategies to ensure business continuity during incidents.

A comprehensive, production-ready toolkit for robustly debugging and monitoring Linear API integrations. This bundle includes features like an instrumented client wrapper for detailed request/response logging, a performance request tracer with summary statistics (avg, p95, max latency), a health check utility, and an environment validator. Ideal for developers setting up logging, performance monitoring, or debugging utilities in a live SaaS environment.

A comprehensive runbook providing step-by-step procedures for managing production incidents related to Linear integrations. It guides users through diagnosing outages, checking API authentication, managing rate limits, and resolving webhook failures, ensuring a quick and effective response across various severities.

LlamaGuard is Meta’s 7–8B safety-specialized LLM that filters both prompts and responses by classifying six threat categories, enabling fast inference via vLLM/SageMaker and integration into NeMo Guardrails for end-to-end moderation.

Practical guide to integrating Claude models: covers API client usage, streaming responses, tool calls, RAG pipelines, document chunking, cost-aware model selection, and anti-pattern warnings for efficient LLM workflows.

A comprehensive guide for diagnosing and fixing common Lokalise API errors and exceptions. This skill details the error response format and provides diagnostic cURL commands for specific HTTP status codes (401, 400, 404, 429, 413, 500, 503). Use it when encountering failed requests, debugging integration issues, or needing to verify API token validity and rate limit status.