Skill UI

Learn how to monitor, analyze, and optimize the expenditure of Large Language Models (LLMs) using Langfuse's advanced analytics suite. This guide covers techniques like automatic token tracking, programmatic cost reporting via the Metrics API, and implementing smart model routing to automatically select the most cost-effective model based on task complexity and input length. Essential for any developer managing AI budgets and ensuring operational efficiency.

This guide details how to establish comprehensive observability for LLM operations using Langfuse. It covers setting up Prometheus metrics (tracking traces, generation duration, and token usage) and visualizing them in Grafana dashboards. Ideal for monitoring application health, optimizing costs, and tracking performance over time.

Automates LaunchDarkly feature flag workflows by listing projects and environments, crafting webhook-driven trigger workflows, deleting flows, and tracking code references through Composio MCP.

This guide details how to implement comprehensive observability for AI agents. It covers monitoring key metrics such as task success rates, step failures, execution duration, and credit consumption. Use this when setting up performance dashboards, configuring real-time alerts (via webhooks/Prometheus), or tracking agent reliability over time.

A comprehensive solution to integrate Linear project management with GitHub Actions CI/CD pipelines. This skill enables automating development workflows by running integration tests, automatically linking Pull Requests (PRs) to issues, transitioning issue states based on PR events, and creating new Linear issues directly from build failures. Ideal for ensuring development quality and maintaining up-to-date project tracking.

This skill provides comprehensive management of the entire issue lifecycle within the Linear project management tool. Users can create new issues, update key metadata (priority, labels, due dates), and automate state transitions through defined workflows. It also supports building parent/sub-issue hierarchies, managing issue relations (blocks, duplicates), and adding comments, making it ideal for automating project tracking and workflow enforcement.

This skill integrates Continuous Integration/Continuous Deployment (CI/CD) pipelines with Linear issue tracking. It automatically detects deployment URLs (e.g., Vercel, Railway), adds detailed deployment comments to relevant Linear issues, and manages state transitions (e.g., moving an issue to 'Review' or 'Done') based on the deployment environment (staging or production). It ensures a seamless link between code commits, deployment status, and project management tickets.

Provides a deep dive into migrating issue tracking data from major platforms like Jira, Asana, and GitHub to Linear. This guide covers the entire lifecycle, including initial workflow assessment, status and priority mapping, data export utilizing API examples, and detailed transformation logic required to ensure data integrity and smooth adoption within Linear.

A comprehensive guide and implementation using TypeScript to establish production-grade observability for Linear API integrations. This includes defining Prometheus metrics (tracking latency, error rates, rate limits, and webhooks), implementing structured logging (using pino), and setting up robust health check endpoints. It ensures full visibility into API performance and system health, critical for mission-critical SaaS applications.

Loki Mode is a multi-agent autonomous startup system that progresses PRD to production with zero human intervention, orchestrating research-enhanced components such as OpenAI SDK, DeepMind, Anthropic, AWS Bedrock, and agent tooling while enforcing RARV reasoning and efficiency tracking.

This workflow is designed for comprehensive industrial asset and location management within the MaintainX platform. It enables users to establish detailed facility location hierarchies, register complex equipment assets (including serial numbers and models), query asset lists, and initiate maintenance work orders. Use it for managing equipment lifecycles, tracking physical assets, and maintaining structured facility records.

A comprehensive guide to minimizing API usage costs by implementing advanced integration patterns. Learn to reduce request volume through response caching with TTL, replacing expensive polling with webhook-driven sync, and utilizing smart polling with change detection filters. Also covers usage tracking and request deduplication for highly efficient system architecture.