Video & Animation

Idiomatic Kotlin patterns, best practices, and conventions for building robust, efficient, and maintainable Kotlin applications with coroutines, null safety, and DSL builders. Use when writing or reviewing Kotlin code and idiomatic structure or null safety is in question.

Kotlin testing patterns with Kotest, MockK, coroutine testing, property-based testing, and Kover coverage. Follows TDD methodology with idiomatic Kotlin practices. Use when writing Kotlin tests with Kotest or MockK, or testing coroutines and checking coverage.

Kubernetes workload patterns, resource management, RBAC, probes, autoscaling, ConfigMap/Secret handling, and kubectl debugging for production-grade deployments. Use when writing or reviewing Kubernetes manifests, or debugging probes, RBAC, autoscaling, or resource limits.

Laravel architecture patterns, routing/controllers, Eloquent ORM, service layers, queues, events, caching, and API resources for production apps. Use when building or reviewing Laravel apps — controllers, Eloquent, service layers, queues, or API resources.

Laravel testing strategies with PHPUnit, Pest, model factories, HTTP tests, Sanctum authentication testing, mocking, and coverage. Use when writing Laravel tests with PHPUnit or Pest, or driving a Laravel feature test-first.

Discover and evaluate Laravel packages via LaraPlugins.io MCP. Use when the user wants to find plugins, check package health, or assess Laravel/PHP compatibility.

Laravel security best practices — authentication, authorization, Eloquent safety, CSRF, XSS prevention, API security, and secure deployment configurations. Use when reviewing Laravel auth, Eloquent safety, CSRF, XSS, API security, or deployment configuration.

Kotlin Coroutines and Flow patterns for Android and KMP — structured concurrency, Flow operators, StateFlow, error handling, and testing. Use when writing coroutines or Flow code on Android or KMP, or debugging cancellation and concurrency.

JetBrains Exposed ORM patterns including DSL queries, DAO pattern, transactions, HikariCP connection pooling, Flyway migrations, and repository pattern. Use when working with the Exposed ORM — DSL or DAO queries, transactions, pooling, or migrations.

Use this skill when retrieving Jira tickets, analyzing requirements, updating ticket status, adding comments, or transitioning issues. Provides Jira API patterns via MCP or direct REST calls.

JPA/Hibernate patterns for entity design, relationships, query optimization, transactions, auditing, indexing, pagination, and pooling in Spring Boot. Use when designing JPA entities or relationships, or when a Hibernate query, transaction, or N+1 problem needs fixing.

Knowledge base management, ingestion, sync, and retrieval across multiple storage layers (local files, MCP memory, vector stores, Git repos). Use when the user wants to save, organize, sync, deduplicate, or search across their knowledge systems.

WireGuard VPN server setup, peer configuration, key generation, split tunneling vs full tunnel routing, and remote access to a home network from mobile and laptop clients. Use when setting up WireGuard for remote access to a home network, or deciding between split and full tunnel routing.

Turn ambiguous or high-impact product and engineering changes into scoped, verifiable acceptance criteria before or alongside implementation. Use when a user asks to clarify a feature, define acceptance criteria, de-risk a security/data/migration/integration change, prepare implementation requirements for another agent, or make a complex request testable. Do not trigger for trivial edits, straightforward fixes, active debugging, code review, or implementation requests whose acceptance conditions are already clear unless the user explicitly invokes this skill.

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Draft cold emails, warm intro blurbs, follow-ups, update emails, and investor communications for fundraising. Use when the user wants outreach to angels, VCs, strategic investors, or accelerators and needs concise, personalized, investor-facing messaging.

Create and update pitch decks, one-pagers, investor memos, accelerator applications, financial models, and fundraising materials. Use when the user needs investor-facing documents, projections, use-of-funds tables, milestone plans, or materials that must stay internally consistent across multiple fundraising assets.

Generate iOS app icons as PNG imagesets for Xcode asset catalogs from SF Symbols (5000+ Apple-native) or Iconify API (275k+ open source icons from 200+ collections). Use when generating icons, creating icon assets, adding icons to asset catalog, or searching for icons for iOS projects.

Pattern for progressively refining context retrieval to solve the subagent context problem. Use when a subagent lacks the context it needs and retrieval must be refined across passes.

Read-only Itô basket and prediction-market data skill. Index the live basket catalog, compare a basket against user-supplied research or a watchlist, build a source-grounded market brief, or draft a non-executable planning worksheet. Use when a user asks to browse or index Itô baskets, compare a basket against notes or a thesis, research prediction-market events/venues/liquidity, or plan a basket or market idea without trading. Never advises, orders, trades, reserves, or executes.

Legacy-project style inheritance skill. Use when the user types /inherit-legacy-style, or when onboarding an AI coding agent onto a hand-written legacy project and you need to prevent

Query live GPU inventory, submit an authenticated Itô fixed-rate RFQ, inspect RFQ or procurement status, revoke device credentials, and run explicitly gated node qualification through the separately installed canonical CLI. Use when a user asks to find H100/H200 capacity, request a fixed compute rate, check Itô compute status, validate GPU nodes, revoke Itô access, or rent or purchase GPU compute and needs the supported boundary explained.

This skill should be used when the user asks to create a hookify rule, write a hook rule, configure hookify, add a hookify rule, or needs guidance on hookify rule syntax and patterns.

Inspect the availability of model serving on a completed Itô compute booking and, when the canonical backend becomes available, hand off an explicitly confirmed serving manifest. Use after ito-compute has booked GPU nodes and the user asks for an OpenAI-compatible endpoint, ito-serve, hosted Kimi, or self-hosted open-weights inference. ECC implements no serving stack of its own.