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Found 2,228 Skills
Translate approved GDDs + architecture into epics — one epic per architectural module. Defines scope, governing ADRs, engine risk, and untraced requirements. Does NOT break into stories — run /create-stories [epic-slug] after each epic is created.
Pre-Production validation — build a production-quality end-to-end build to confirm the full game loop is achievable before committing to Production. Run after GDDs, architecture, and UX specs are complete. Produces a PROCEED/PIVOT/KILL verdict that gates the Pre-Production → Production transition.
Write dense storyboard-grid prompts for short-form image or previsualization workflows. Use this when a generation controller needs a 6-9 panel grid with hook logic, visible actions, product timing, and negative constraints before image or video request architecture.
Workload-aware architecture design for Apache Doris. MUST USE when designing data architectures, choosing between data models, planning ingestion strategies, sizing clusters, or translating business requirements into Apache Doris system designs. Complements doris-best-practices with decision frameworks and sizing-first workflow. Use when user describes a workload involving: IoT, sensor data, telemetry, real-time analytics, dashboard, log analysis, log search, CDC sync, time-series, device monitoring, point query service, ad-hoc analytics, lakehouse federation, ETL/ELT pipeline, report analytics, clickstream, user behavior, observability, metrics, fleet tracking, or any OLAP workload requiring table design from scratch. Also triggers on prompts like: "design a table for...", "how should I store...", "build an architecture for...", "we have X devices sending data every Y seconds", "recommend a cluster size for...", "what data model should I use for...", "we need to ingest X GB/day", "migrate from MySQL/PostgreSQL to Apache Doris". Also use for legacy analytics/search/serving stack consolidation prompts even when Apache Doris is not named explicitly, including replacing or migrating from Impala, Kudu, Elasticsearch/ES, Greenplum, Presto, HBase, Hive, Hadoop, Redis, or Lambda-style multi-engine data platforms.
Monocular depth estimation using Metric Depth Anything v2 or Relative Depth Anything architectures. Predicts per-pixel depth from single RGB images. Use when training, evaluating, exporting, or running inference for a TAO monocular depth model. Trigger phrases include "train monocular depth", "DepthAnything v2", "metric depth from single image", "monocular depth estimation".
CQRS - Command Query Responsibility Segregation. Use when implementing DDD patterns, separating read/write models, event sourcing, or building scalable architectures with heterogeneous performance requirements.
Analyze a codebase to produce an interactive knowledge graph for understanding architecture, components, and relationships
Voice agents represent the frontier of AI interaction - humans speaking naturally with AI systems. The challenge isn't just speech recognition and synthesis, it's achieving natural conversation flow with sub-800ms latency while handling interruptions, background noise, and emotional nuance. This skill covers two architectures: speech-to-speech (OpenAI Realtime API, lowest latency, most natural) and pipeline (STT→LLM→TTS, more control, easier to debug). Key insight: latency is the constraint. Hu
Help users evaluate emerging technologies. Use when someone is assessing new tools, making build vs buy decisions, evaluating AI vendors, or deciding on technical architecture.
Create detailed technical specifications, requirements documents, design documents, and system architecture specs. Use when writing technical specs, requirements docs, or design documents.
Build 2D browser games with Phaser 3 (JS/TS): scenes (Boot/Menu/Game/UI), sprites/animations, input, Arcade/Matter physics, tilemaps (Tiled), asset loading, and performance patterns. Use for prompts like 'Phaser scene', 'Arcade physics', 'tilemap', 'Phaser 3 game architecture'.
Manage monorepo architectures using Lerna, Turborepo, and Nx. Configure workspaces, dependency versioning, and cross-package testing.