Total 35,510 skills
Showing 12 of 35510 skills
A session continuity loop where the frog is disposable but the pad is not.
Tinybird Python SDK for defining datasources, pipes, and queries in Python. Use when working with tinybird-sdk, Python Tinybird projects, or data ingestion and queries in Python.
Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics.
Expert blueprint for data-oriented design using Resource/RefCounted classes (item databases, character stats, reusable data structures). Covers typed arrays, serialization, nested resources, and resource caching. Use when implementing data systems OR inventory/stats/dialogue databases. Keywords Resource, RefCounted, ItemData, CharacterStats, database, serialization, @export, typed arrays.
Expert blueprint for low-level server access (RenderingServer, PhysicsServer2D/3D, NavigationServer) using RIDs for maximum performance. Bypasses scene tree overhead for procedural generation, particle systems, and voxel engines. Use when nodes are too slow OR managing thousands of objects. Keywords RenderingServer, PhysicsServer, NavigationServer, RID, canvas_item, body_create, low-level, performance.
Expert blueprint for horror games including tension pacing (sawtooth wave: buildup/peak/relief), Director system (macro AI controlling pacing), sensory AI (vision/sound detection), sanity/stress systems (camera shake, audio distortion), lighting atmosphere (volumetric fog, dynamic shadows), and "dual brain" AI (cheating director + honest senses). Use for psychological horror, survival horror, or atmospheric games. Trigger keywords: horror_game, tension_pacing, director_system, sensory_perception, sanity_system, volumetric_fog, AI_reaction_time.
Plan and execute large refactor or rewrite efforts efficiently with parallel multi-agent analysis and implementation. Use when a user asks to refactor many files, split workstreams, analyze a target code area, and coordinate sub-agents with clear ownership and dependency-aware execution.
Set up performance benchmarks and CodSpeed harness for a project. Use this skill whenever the user wants to create benchmarks, add performance tests, set up CodSpeed, configure codspeed.yml, integrate a benchmarking framework (criterion, divan, pytest-benchmark, vitest bench, go test -bench, google benchmark), or when the user says 'add benchmarks', 'set up perf tests', 'create a benchmark', 'benchmark this', or wants to measure performance of their code for the first time. Also trigger when the optimize skill needs benchmarks that don't exist yet.
Agent skill for benchmark-suite - invoke with $agent-benchmark-suite
Agent skill for memory-coordinator - invoke with $agent-memory-coordinator
Agent skill for tdd-london-swarm - invoke with $agent-tdd-london-swarm
Workflow creation, execution, and template management. Automates complex multi-step processes with agent coordination. Use when: automating processes, creating reusable workflows, orchestrating multi-step tasks. Skip when: simple single-step tasks, ad-hoc operations.