Skill UI

Playbook for building first-person shooters: first-person move/look controller, hitscan or projectile shooting, weapons, health, enemy AI, and tuning of time-to-kill, recoil, and spread. Use when developing an FPS or adjusting aim feel and combat balance.

This skill orchestrates advanced Machine Learning training workflows on dedicated compute clusters. It manages complex stages (pre-training, fine-tuning, RL) by ensuring strict adherence to immutable manifests, fresh booking entitlements, and multi-step confirmation gates. It acts as a canonical interface for job submission, emphasizing security, idempotency, and resource validation before execution.

This skill generates comprehensive test data spreadsheets for compliance teams to validate their sanctions screening systems. It pulls new designations and deliberate variations from major global lists (OFAC, OFSI, and EU). The test verifies both the list's coverage (catching the newest designations) and the system's fuzzy matching tuning (catching realistic name variations, transpositions, and aliases). Ideal for screening QA, regression testing, and ensuring regulatory compliance.

A comprehensive guide to tuning game physics parameters, including mass, gravity, drag, and continuous collision detection (CCD). It addresses common stability issues like jitter and tunneling by correctly separating the fixed-timestep simulation (physics updates) from the variable-rate rendering (visual updates) using interpolation. Essential for creating predictable and responsive game motion across various hardware.

A comprehensive playbook for designing and implementing 'feel-good' 2D platformers, such as Mario or Celeste. This skill focuses on the compositional elements: tuning jump physics using variables like coyote time, jump buffering, and variable jump height. It teaches how to achieve responsive, satisfying moment-to-moment movement for side-scrolling games.

Learn to configure 3D physics in Unity 6.3 LTS using PhysX. Covers Rigidbody movement, forces, colliders, triggers, and collision layers. Essential for handling OnCollisionEnter, tuning layers, raycasting, and joints. Includes best practices for FixedUpdate, linearVelocity, and avoiding common pitfalls like transform manipulation.

This skill provides expert patterns for implementing Algolia search, including indexing strategies, React InstantSearch integration, and relevance tuning. It covers search API usage, typeahead functionality, autocomplete, and faceted search implementation. Use this for adding robust search functionality to web applications and optimizing search results.

Optimize end-to-end application performance using specialized agents for profiling, observability, database/backend tuning, frontend loading, CDN optimization, and load testing. Use when coordinating cross-stack performance improvements, establishing baselines, identifying bottlenecks, and setting up monitoring for sustained reliability.

Provision and manage Amazon RDS relational databases including PostgreSQL, MySQL, and SQL Server. Configure backups, replication, security, and monitoring using AWS CLI. Ideal for deploying production-grade managed databases with high availability and performance tuning.

This skill covers provisioning and managing Azure SQL Database and Cosmos DB instances. It includes configuring security settings, setting up backups, and implementing geo-replication strategies. Users will learn to create servers, databases, and elastic pools using Azure CLI commands. It also addresses firewall rules, network security, failover groups, and performance tuning for production environments. Ideal for DevOps engineers and cloud administrators deploying managed databases on Azure.

This Python SDK enables interaction with Azure Blob Storage for unstructured data. It supports uploading, downloading, listing, and managing blobs and containers. Includes authentication, SAS tokens, async operations, and performance tuning for efficient cloud storage workflows.

Guide to selecting and optimizing embedding models for vector search and RAG applications, covering model comparison, chunking, fine-tuning, and dimension reduction.