Skill UI

Automatically detects and loads specialized agent instructions from the `AGENTS.md` file in the current working directory. This skill seamlessly integrates project-specific rules and behavioral guidelines into the AI's session context, ensuring the AI operates according to project standards without manual intervention. It is crucial for maintaining specialized agent behaviors across different development tasks and directory changes.

Analyzes query workloads with the database-index-advisor plugin to spot missing or unused indexes and recommends creations or removals to boost performance and reclaim storage.

Analyzes query workloads with the database-index-advisor plugin to spot missing or unused indexes and recommends creations or removals to boost performance and reclaim storage.

Document that explains how to automate API Ninjas operations via Composio’s Rube MCP integration: search for tools, ensure an active API Ninjas connection, and run workloads with schema-compliant inputs and memory/session handling.

This tool provides comprehensive cost management for Apollo.io API usage. It optimizes credit expenditure by implementing a daily budget tracker, preventing double-enrichment through deduplication, and using a lead scoring mechanism to ensure credits are only spent on high-potential leads. Ideal for large-scale data enrichment tasks to minimize API costs.

This skill provides comprehensive guidance on implementing high-performance, non-blocking applications in Python. It utilizes asyncio, async/await, and advanced concurrency patterns to handle I/O-bound workloads efficiently. Ideal for building async web APIs, real-time systems, and concurrent data processing.

This is a low-level SDK for Java designed to create and manage persistent AI agents within Azure AI. It provides comprehensive tools for handling the entire agent lifecycle, including creating agents, managing conversation threads, sending messages, running agent processes, and cleaning up resources. Ideal for building robust, stateful AI applications requiring fine-grained control over agent interactions.

This is a low-level SDK for Java designed to create and manage persistent AI agents within Azure AI. It provides comprehensive tools for handling the entire agent lifecycle, including creating agents, managing conversation threads, sending messages, running agent processes, and cleaning up resources. Ideal for building robust, stateful AI applications requiring fine-grained control over agent interactions.

A specialized skill for writing highly efficient, memory-safe, and robust C code. This guide focuses on best practices for systems programming, including rigorous memory management (malloc/free), advanced pointer arithmetic, POSIX compliance, multi-threading (pthreads), and embedded systems constraints. It emphasizes using static analysis tools, implementing comprehensive error handling, and ensuring performance through proper profiling. Ideal for complex, low-level system tasks.

Guides ClickHouse database architects through schema designs, query optimization, ingestion strategies, and monitoring techniques tailored for high-performance analytical workloads.

Guides GCP users through automating Cloud Scheduler job creation with best practices, ready-to-run code, and validation, ideal for implementing cron-driven workloads across compute, storage, BigQuery, Vertex AI, and Cloud Run.

Automates AWS CloudFront distribution setup with step-by-step guidance, production-ready configurations, and validation against best practices for compute, storage, networking, and serverless workloads.