Skill UI

Mandates Taskwarrior integration for every coding request by decomposing work into tracked tasks, starting them, syncing Timewarrior time tracking, and enforcing the full add→start→done lifecycle before writing code.

Automate Algolia tasks through Composio’s toolkit with Rube MCP; always search tools first, confirm active connections, and execute schema-compliant workflows with RUBE_MULTI_EXECUTE_TOOL while tracking sessions and pagination.

This skill provides comprehensive methods for building event-driven integrations with Apollo.io. Since Apollo lacks native webhooks, it covers advanced techniques like polling the Contacts API, tracking contact stage changes, monitoring sequence engagement, and automating follow-up tasks. Ideal for achieving real-time CRM data synchronization and workflow automation.

This skill provides comprehensive methods for building event-driven integrations with Apollo.io. Since Apollo lacks native webhooks, it covers advanced techniques like polling the Contacts API, tracking contact stage changes, monitoring sequence engagement, and automating follow-up tasks. Ideal for achieving real-time CRM data synchronization and workflow automation.

This skill provides a comprehensive, actionable overview of the Conductor project's status. It aggregates information from project plans, active tracks, and detailed specifications to display overall progress, identify next critical tasks, and flag potential blockers. Use it when you need a high-level dashboard view of project health and required actions.

A comprehensive pattern for building robust and cost-efficient LLM application pipelines. This guide details combining model routing based on task complexity, immutable cost tracking, limited retry logic, and prompt caching to manage API expenditures while maintaining high quality. Essential for production systems handling variable-complexity, high-volume tasks.

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 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.

A comprehensive guide to optimizing LLM API usage within LangChain frameworks. Techniques include implementing token usage tracking, model tiering to route tasks based on complexity, utilizing caching to eliminate duplicate calls, prompt compression for efficiency, and enforcing strict budget limits to manage operational costs effectively.

This comprehensive guide covers the entire MLOps lifecycle, specializing in building robust, scalable, and production-grade Machine Learning systems. Expertise includes orchestrating complex ML pipelines using Kubeflow, Airflow, Prefect, and cloud-native services (AWS SageMaker, Azure ML, GCP Vertex AI). It covers experiment tracking (MLflow, W&B), model versioning, model registries, infrastructure as code (Terraform), and container deployment using Kubernetes. Ideal for engineers tasked with moving ML models from research to reliable, managed production environments.

Converts product or technical specs into detailed Notion implementation plans, tasks, and progress logs so Claude code can execute requirements tracking from inception to completion.

A comprehensive guide to integrating Sentry into continuous integration and continuous deployment (CI/CD) pipelines (e.g., GitHub Actions, GitLab CI, CircleCI). This skill automates complex tasks such as creating releases, uploading source maps for readable stack traces, associating commits, and tracking deployment environments, ensuring rapid and accurate debugging of production errors.