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概要と使いどころ
Expert blueprint for physics queries using RayCast, ShapeCast, and DirectSpaceState. Covers hit detection, volume overlap, mouse picking, and high-performance server-side intersection queries. Use when implementing projectiles, LOS, terrain grounding, or AI sensors. Keywords raycast, shapecast, direct_space_state, intersect_ray, intersect_shape, PhysicsRayQueryParameters, collision mask, mouse picking.
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 First-Person Shooters: fps_camera_look, fps_movement_logic, hitscan_weapon_query, weapon_bobbing_system, procedural recoil, and FPS NEVER rules. Shared TPS/cover theory links to godot-genre-shooter. Keywords: FPS, movement physics, weapon bobbing, camera sway, hitscan, viewmodel, air control.
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。
Bevy ECS skill for spatial queries. Keywords: Bevy, raycast, shapecast, picking, physics query.
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。
Bevy ECS skill for entity composition. Keywords: Bevy, ECS, Component, Query, 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。
Designer subsystem patterns for LlamaFarm. Covers React 18, TanStack Query, TailwindCSS, and Radix UI.
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。
React 18 patterns for LlamaFarm Designer. Covers components, hooks, TanStack Query, and testing.
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。
Query A-share and Chinese financial market data via multiple data sources. Tier-1 paid source is iFind (同花顺, covers stocks/funds/macro/bonds/HK-US/ESG/index-sectors). Tier-2 free source is AkShare (行情/财报/行业/指数). Use whenever the agent needs Chinese financial data — compatible with 沪深 A 股, 科创板, 创业板, 北交所, and 港股通 stocks.
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。
Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.
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。
Optimize slow React Router loaders by eliminating redundant DB queries, creating slim query variants, and parallelizing independent fetches. Use proactively when writing or reviewing loader code that calls domain operations services (e.g. CourseOperationsService, VideoOperationsService), or when triaging a slow page load.
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。
SwiftData class inheritance patterns for hierarchical models with type-based querying, polymorphic relationships, and when to choose inheritance vs enums. Use when designing SwiftData model hierarchies.
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。
Deep dive into SwiftData design patterns and best practices. Covers schema design, query patterns, repository pattern, and performance optimization. Use when designing data models or improving SwiftData usage.
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。
SwiftData skills — class inheritance patterns for hierarchical models, type-based querying, polymorphic relationships, and inheritance-vs-enum decisions. Use when designing SwiftData model hierarchies.
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。
Query a user's TrailSnap photo library through scoped MCP tools to find photos, reconstruct memories, build person timelines, create evidence-backed narratives, or propose an album plan for explicit in-app approval. Use for the user's own TrailSnap library; never claim a proposal was executed or changed the library.
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。
Query photos, albums, locations, tags, and people from a TrailSnap instance through its command-line client. Use when TrailSnap MCP tools are unavailable and the user asks about their own photo library; Agent Tokens are read-only, so do not use this skill to mutate library data.
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 knowledge for Azure Digital Twins development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when modeling DTDL graphs, integrating IoT Hub/ADx, configuring endpoints/routes, securing access, or tuning query units, and other Azure Digital Twins related development tasks. Not for Azure IoT Hub (use azure-iot-hub), Azure IoT Central (use azure-iot-central), Azure IoT Operations (use azure-iot-operations).
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。
Checks whether a company's own website mentions a specific keyword, using one simple Google site: query per keyword through a SERP API, and turns the hit into a copy-ready line. Triggers on "does their site mention X", "site: search", "find companies whose website says X", "filter this list by a keyword on their site", "check if they talk about X", "google search enrichment". Outputs site_keyword_hit plus a one-clause personalization line with an evidence URL.
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。
Local user-profile maintenance skill for Codex, Claude Code, OpenClaw, OpenCode, and other agent harnesses. Use only when the user explicitly invokes $user-profile-keeper to create, initialize, update, query, correct, delete, export, or audit a local persistent user profile. It can extract durable collaboration preferences, requirement-expression habits, capability boundaries, recurring omissions, risk preferences, privacy boundaries, and typical events from the current session into auditable, confirmable, retractable local profile data. Do not auto-invoke, upload profile data, or replace task-clarifier's normal clarification flow.
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。
LlamaIndex 官方用户文档离线知识库，用于检索并回答 LlamaIndex Python 框架的安装、RAG、数据加载、索引、检索与查询、Agent、Workflow、模型、Embedding、向量库、评估、可观测性、部署、LlamaCloud 和 LlamaParse 等问题，也可生成有文档依据的示例代码与排障建议。当用户提到 LlamaIndex、llama-index、LlamaParse、VectorStoreIndex、QueryEngine、Retriever、AgentWorkflow 或相关集成用法时使用；纯源码贡献、内部实现审查或与 LlamaIndex 无关的通用 AI 问题不使用。
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 this skill AUTOMATICALLY before writing any Higgsfield prompt. Query the memory databases for relevant past failures and pre-apply known fixes before the user even hits generate. Triggers include: any request to write a Higgsfield prompt, any use of the higgsfield-prompt skill, any mention of generating a video or image on Higgsfield, any MCSLA prompt construction. This skill should run SILENTLY in the background — don't announce it, just apply what's known. If the databases are empty, skip silently and proceed with normal prompt generation.
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。
Query AwardWallet for loyalty program balances, elite status, and transaction history. Use when checking points inventory, airline status, or planning trips on points.
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 cost-safe geospatial SQL for BigQuery, DuckDB, Snowflake, Wherobots, and Postgres and/or render results on an interactive Dekart map.
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。
Find web sources with query-relevant page excerpts and optional full-page content, and discover workflows, data APIs, and indexes. Use for web research or finding structured records, listings, transcripts, and datasets. Supports semantic tool discovery, domain matching, and progressive catalogue browsing.
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 for blue-team threat hunting, detection engineering with Sigma/YARA, SIEM query design, and incident detection validation.
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 the user asks what the codebase intel knows, or runs /gsd-intel query, status, diff, or refresh. Queries or rebuilds the .planning/intel/ files, and stops with a disabled message when intel is off in .planning/config.json.
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。