「systems」の検索結果

Expert patterns for Godot audio including AudioStreamPlayer variants (2D positional, 3D spatial), AudioBus mixing architecture, dynamic effects (reverb, EQ,compression), audio pooling for performance, music transitions (crossfade, bpm-sync), and procedural audio generation. Use for music systems, sound effects, spatial audio, or audio-reactive gameplay. Trigger keywords: AudioStreamPlayer, AudioStreamPlayer2D, AudioStreamPlayer3D, AudioBus, AudioServer, AudioEffect, music_crossfade, audio_pool, positional_audio, reverb, bus_volume.

日本語の概要は準備中です。原文の説明を表示しています。

Expert blueprint for RPG stat systems (attributes, leveling, modifiers, damage formulas) using Resource-based stats, stackable modifiers, and derived stat calculations. Use when implementing character progression OR equipment/buff systems. Keywords stats, attributes, leveling, modifiers, CharacterStats, derived stats, damage calculation, XP.

日本語の概要は準備中です。原文の説明を表示しています。

Expert blueprint for quest tracking systems (objectives, progress, rewards, branching chains) using Resource-based quests, signal-driven updates, and AutoLoad managers. Use when implementing RPG quests or mission systems. Keywords quest, objectives, Quest Resource, QuestObjective, signal-driven, branching, rewards, AutoLoad.

日本語の概要は準備中です。原文の説明を表示しています。

Expert blueprint for turn-based combat with turn order, action points, phase management, and timeline systems for strategy/RPG games. Covers speed-based initiative, interrupts, and simultaneous turns. Use when implementing turn-based combat OR tactical systems. Keywords turn-based, initiative, action points, phase, round, turn order, combat.

日本語の概要は準備中です。原文の説明を表示しています。

Expert patterns for game economies including currency management (multi-currency, wallet system), shop systems (buy/sell prices, stock limits), dynamic pricing (supply/demand), loot tables (weighted drops, rarity tiers), and economic balance (inflation control, currency sinks). Use for RPGs, trading games, or resource management systems. Trigger keywords: EconomyManager, currency, shop_item, loot_table, dynamic_pricing, buy_sell_spread, currency_sink, inflation, item_rarity.

日本語の概要は準備中です。原文の説明を表示しています。

Expert blueprint for stealth games (Splinter Cell, Hitman, Dishonored, Thief) covering AI detection systems, vision cones, sound propagation, alert states, light/shadow mechanics, and systemic design. Use when building stealth-action, tactical infiltration, or immersive sim games requiring enemy awareness systems. Keywords vision cone, detection, alert state, sound propagation, light level, systemic AI, gradual detection.

日本語の概要は準備中です。原文の説明を表示しています。

Expert patterns for 2D/3D camera control including smooth following (lerp, position_smoothing), camera shake (trauma system), screen shake with frequency parameters, deadzone/drag for platformers, look-ahead prediction, and camera transitions. Use for player cameras, cinematic sequences, or multi-camera systems. Trigger keywords: Camera2D, Camera3D, SpringArm3D, position_smoothing, camera_shake, trauma_system, look_ahead, drag_margin, camera_limits, camera_transition.

日本語の概要は準備中です。原文の説明を表示しています。

Expert blueprint for fighting games including frame data (startup/active/recovery frames, advantage on hit/block), hitbox/hurtbox systems, input buffering (5-10 frames), motion input detection (QCF, DP), combo systems (damage scaling, cancel hierarchy), character states (idle/attacking/hitstun/blockstun), and rollback netcode. Based on FGC competitive design. Trigger keywords: fighting_game, frame_data, hitbox_hurtbox, input_buffer, motion_inputs, combo_system, rollback_netcode, cancel_system, advantage_frames.

日本語の概要は準備中です。原文の説明を表示しています。

Expert patterns for combat systems including hitbox/hurtbox architecture, damage calculation (DamageData class), health components, combat state machines, combo systems, ability cooldowns, and damage popups. Use for action games, RPGs, or fighting games. Trigger keywords: Hitbox, Hurtbox, DamageData, HealthComponent, combat_state, combo_system, ability_cooldown, invincibility_frames, damage_popup.

日本語の概要は準備中です。原文の説明を表示しています。

Expert blueprint for idle/clicker games including big number handling (mantissa + exponent system), exponential growth curves (cost_growth_factor 1.15x), generator systems (auto-producers), offline progress calculation, prestige systems (reset for permanent multipliers), number formatting (K/M/B suffixes, scientific notation). Use for incremental games, idle games, or cookie clicker derivatives. Trigger keywords: idle_game, big_number, exponential_growth, generator_system, offline_progress, prestige_system, number_formatting.

日本語の概要は準備中です。原文の説明を表示しています。

Expert patterns for Godot audio including AudioStreamPlayer variants (2D positional, 3D spatial), AudioBus mixing architecture, dynamic effects (reverb, EQ,compression), audio pooling for performance, music transitions (crossfade, bpm-sync), and procedural audio generation. Use for music systems, sound effects, spatial audio, or audio-reactive gameplay. Trigger keywords: AudioStreamPlayer, AudioStreamPlayer2D, AudioStreamPlayer3D, AudioBus, AudioServer, AudioEffect, music_crossfade, audio_pool, positional_audio, reverb, bus_volume.

日本語の概要は準備中です。原文の説明を表示しています。

Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.

日本語の概要は準備中です。原文の説明を表示しています。

Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full ASM JSON, flattened CSV for easy import, and exportable Python code for data engineers. Common triggers include converting instrument files, standardizing lab data, preparing data for upload to LIMS/ELN systems, or generating parser code for production pipelines.

日本語の概要は準備中です。原文の説明を表示しています。

Advanced architecture stress analysis methodology for designing systems that survive unknown stresses. Load when --residuality flag is used or when designing high-uncertainty, mission-critical systems.

日本語の概要は準備中です。原文の説明を表示しています。

Vector database implementation for AI/ML applications, semantic search, and RAG systems. Use when building chatbots, search engines, recommendation systems, or similarity-based retrieval. Covers Qdrant (primary), Pinecone, Milvus, pgvector, Chroma, embedding generation (OpenAI, Voyage, Cohere), chunking strategies, and hybrid search patterns.

日本語の概要は準備中です。原文の説明を表示しています。

Manage Linux systems covering systemd services, process management, filesystems, networking, performance tuning, and troubleshooting. Use when deploying applications, optimizing server performance, diagnosing production issues, or managing users and security on Linux servers.

日本語の概要は準備中です。原文の説明を表示しています。

When designing distributed systems for scalability, reliability, and consistency. Covers CAP/PACELC theorems, consistency models (strong, eventual, causal), replication patterns (leader-follower, multi-leader, leaderless), partitioning strategies (hash, range, geographic), transaction patterns (saga, event sourcing, CQRS), resilience patterns (circuit breaker, bulkhead), service discovery, and caching strategies for building fault-tolerant distributed architectures.

日本語の概要は準備中です。原文の説明を表示しています。

Optimizing vector embeddings for RAG systems through model selection, chunking strategies, caching, and performance tuning. Use when building semantic search, RAG pipelines, or document retrieval systems that require cost-effective, high-quality embeddings.

日本語の概要は準備中です。原文の説明を表示しています。

Designs layout systems and responsive interfaces including grid systems, flexbox patterns, sidebar layouts, and responsive breakpoints. Use when structuring app layouts, building responsive designs, or creating complex page structures.

日本語の概要は準備中です。原文の説明を表示しています。

Use when reviewing, designing, or modifying Java enterprise systems that may support intermediary services, hosting services, online platforms, marketplaces, content moderation, recommender systems, advertising delivery, complaint workflows, transparency reporting, or systemic-risk evidence under the EU Digital Services Act. This should trigger for requests such as Review a Java online platform for DSA controls; Design notice-and-action or appeal workflows; Add recommender, ad transparency, moderation, audit, researcher access, or privacy-safe observability evidence; Assess online-platform transparency controls before production release. Part of Plinth Toolkit

日本語の概要は準備中です。原文の説明を表示しています。

Use when a problem under exploration needs its surrounding system context identified before design begins — Existing systems, Integrations, Ownership, and External dependencies. This should trigger when an issue's Context Mapping point of view needs evaluation, or when a maintainer directly asks to map the systems, integrations, owners, and external dependencies relevant to a problem. Part of Plinth Toolkit

日本語の概要は準備中です。原文の説明を表示しています。

This skill should be used when designing or implementing systems with multiple AI agents that coordinate to accomplish tasks. Triggers on "multi-agent", "orchestrator", "sub-agent", "coordination", "delegation", "parallel agents", "sequential pipeline", "fan-out", "map-reduce", "spawn agents", "agent hierarchy".

日本語の概要は準備中です。原文の説明を表示しています。

Build automated billing systems for recurring payments, invoicing, subscription lifecycle, and dunning management. Use when implementing subscription billing, automating invoicing, or managing recurring payment systems.

日本語の概要は準備中です。原文の説明を表示しています。

Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.

日本語の概要は準備中です。原文の説明を表示しています。