Skill UI

An advanced AI-driven framework for holistic performance engineering of multi-agent systems. It provides coordinated profiling, workload distribution, and cost-aware orchestration across various domains (database, application, frontend). Use this tool to identify bottlenecks, improve throughput, enhance reliability, and manage resource constraints in complex agent workflows.

A guide for pausing and asking targeted questions whenever requirements are vague, ensuring the team locks in objectives, scope, constraints, and acceptance criteria before any implementation begins.

A guide for pausing and asking targeted questions whenever requirements are vague, ensuring the team locks in objectives, scope, constraints, and acceptance criteria before any implementation begins.

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.

Automate Botstar via Composio’s Rube MCP by discovering current tool schemas, managing Botstar connections, and executing workflows through RUBE_SEARCH_TOOLS and RUBE_MULTI_EXECUTE_TOOL while respecting schema constraints.

A comprehensive guide to structuring effective custom prompts for AI coding assistants like Cursor. Learn the four components of prompt anatomy (Context, Task, Constraints, Format), and utilize reusable templates for complex tasks such as feature implementation, bug fixing, code review, and test generation. Master advanced techniques like Chain of Thought and Few-Shot examples to ensure high-quality, consistent code output.

A comprehensive reference guide for structuring development projects within the Cursor IDE. It details best practices for directory layout, defining layered rules (covering global conventions, security constraints, and technology-specific patterns like API routes and database access), and optimizing indexing strategies. This ensures maximum AI effectiveness, improves code maintainability, and streamlines the entire development workflow.

Generates realistic database seed data and scripts for development or testing, leveraging Faker libraries to respect schema constraints, maintain relationships, and allow configurable volumes for quick population of demo or test environments.

This guide details the usage limits, quotas, and rate limits across Granola's various plans (Basic, Business, Enterprise). It helps users understand the differences between tiers, the constraints on meetings, meeting history, and the Enterprise API, ensuring users can select the appropriate plan to avoid service interruptions and optimize API usage.

Guidance lets you wrap LLM calls with grammars, regex, and selection constraints to ensure valid JSON/XML/code, enforce formats, heal tokens, and orchestrate multi-step workflows via Pythonic context managers for production-ready automation.

Guides implementing Kubernetes NetworkPolicy, RBAC, PodSecurityPolicy, Pod Security Standards, and OPA Gatekeeper constraints to enforce defense-in-depth across clusters, covering multi-tenant protection, admission control, and Istio service mesh policies.

This comprehensive skill manages the entire lifecycle of database testing, ensuring data integrity and system reliability. It covers setting up isolated test environments (using Docker or in-memory databases), executing migrations, and implementing robust test isolation strategies (such as transaction rollback). Use cases include verifying CRUD operations, validating referential constraints, performance benchmarking (EXPLAIN ANALYZE), and ensuring backward compatibility across multiple databases (PostgreSQL, MySQL, MongoDB) and ORMs.