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概要と使いどころ
This skill recommends educating patients and families about the clinical features of remission in Cushing's syndrome when a patient achieves biochemical remission after treatment. Use when a CS patient has postoperative normal cortisol levels, reports symptom improvement, and requires guidance on long-term expectations and monitoring for recurrence.
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。
Add Wasp's built-in features to your app: auth, email, jobs, and more. These are full-stack, batteries-included features that Wasp handles for you. Use when the user wants to add meta tags, authentication (email, social auth providers), email sending, database setup, styling (tailwind, shadcn), or other Wasp-powered functionality.
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。
Guide for creating and managing slash commands in Claude Code. Use when (1) creating new slash commands, (2) learning command syntax and features, (3) deciding between commands vs skills, (4) implementing advanced command features (arguments, hooks, bash execution), or (5) organizing and managing command libraries.
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。
Systematic testing methodology for exhaustive branch coverage, edge case identification, and production bug prevention. Use when PR review reveals incomplete test coverage, when tests pass but users report bugs, when code changes break existing features, when verifying all branches and edge cases before merge, when analyzing "it works on my machine" issues, when planning test strategy for new features, or when debugging flaky tests and race conditions.
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。
Fornece orientação para treinar e analisar Autoencodificadores Esparsos (SAEs) usando SAELens para decompor ativações de redes neurais em features interpretáveis. Use ao descobrir features interpretáveis, analisar superposição ou estudar representações monossemânticas em modelos de linguagem.
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。
Load this skill when building any web feature, reviewing architecture decisions, or evaluating JavaScript dependencies. Under no circumstances build features that break completely when JavaScript is unavailable or fails. Absolutely always start with semantic HTML, layer CSS enhancements, and add JavaScript as the final, optional layer. Prioritize resilience and universal access over cutting-edge features.
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。
METAINFORMANT rules for directory src/metainformant/ml/features. Use when editing, adding tests, or reviewing code under this path. Read the linked AGENTS.md first; use uv only, write outputs to output/, real implementations.
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。
Make a WooCommerce plugin HPOS-compatible (High-Performance Order Storage, default-on in WC 10.x) — declare via FeaturesUtil::declare_compatibility on before_woocommerce_init, replace $wpdb->postmeta / WP_Query order code with wc_get_orders + WC_Order::get_meta / update_meta_data, gate runtime branches on OrderUtil::custom_orders_table_usage_is_enabled, build admin hook names dynamically with OrderUtil::get_order_admin_screen (HPOS = woocommerce_page_wc-orders, legacy = shop_order). Use when scaffolding an order-touching plugin, auditing existing code for HPOS readiness, or fixing post-WC-10 silent breakage. Triggers on shop_order, get_post_meta with order context, FeaturesUtil, OrderUtil, custom_order_tables, before_woocommerce_init.
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。
リポジトリの構造・技術スタック・機能一覧・セットアップ手順を動的に解析し、 包括的なドキュメントを自動生成するスキル。言語・フレームワーク問わず汎用的に動作する。 Use this skill whenever the user asks to: - Explain a repository / リポジトリの説明 / リポジトリの概要 - Generate a README / README生成 / README作成 - Understand project structure / プロジェクト構成を教えて / 構造を説明して - Learn how to run a project / 使い方を教えて / 動かし方 / セットアップ方法 - Get a repo overview / repo overview / explain this repo / what does this repo do - List features / 機能一覧 / このプロジェクトは何ができる？ - Onboard to a new codebase / コードベースのキャッチアップ / 新しいリポジトリに入った - "このリポジトリ何？" "プロジェクトの全体像" "how to run this project" - "コードの全体を把握したい" "ドキュメントを整備して" "技術スタックを知りたい" This skill is especially useful when joining a new project, onboarding team members, or when a repository lacks proper documentation. It works with ANY repository regardless of programming language, framework, or project type.
End-to-end Android indie idea workflow — feature-build phase only (no monetization). Phased — discover (if no idea) → generate 2 candidates → refine scope (offline/online, sharing, MVP vs full, core-value features) → risk/reward/tradeoff analysis when scoping down → emit idea brief. Use for greenfield app concepts, new feature ideation, idea discovery, or pre-design discovery before writing a design document. Triggers — new app idea, feature concept, indie dev brainstorm, validate idea, refine idea, what should I build, find an app idea, idea pipeline, I have no idea, help me find an app idea, scope down, MVP scoping, core value features.
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。
Drive a whole tdmcp feature BACKLOG to completion as resumable, wave-by-wave releases — the campaign layer ABOVE tdmcp-pipeline/tdmcp-feature-lead. Use whenever the user wants to implement an ENTIRE backlog or discovery file (e.g. _workspace/discovery*/FEATURE_BACKLOG*.md), 'all the features', many features across multiple releases, or a long autonomous build campaign, AND for every follow-up: continue/resume the campaign, run the next wave, re-run a failed wave, fold in QA results, or check campaign status. Backed by a ledger.json so re-running is idempotent (skips shipped work, resumes interrupted work) and resilient (retry-once then quarantine-and-continue). For a SINGLE feature or one small batch, use tdmcp-pipeline instead; this skill is for the whole ledger.
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。
Survey the whole tdmcp project and produce a prioritized list of NEW features it could implement — across artist controls, CLI/DX, AI/LLM integration, and TouchDesigner depth. Use whenever the user wants to brainstorm, discover, survey, list, or audit what features/tools/effects/controls/commands/prompts/capabilities tdmcp *could* add, asks 'what could we build / what's missing / what are the opportunities / ideas for the project', or wants a feature backlog or gap analysis. Also for follow-ups: re-run, refresh, update, re-survey, deepen, or re-prioritize the backlog, or survey just one surface (e.g. 'CLI ideas only'). This is the IDEATION harness — it produces a list to decide from; it does NOT build. When the user has already chosen a feature and wants it implemented/shipped/added, use tdmcp-pipeline instead.
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, review, or improve maps and location features in iOS/macOS apps using MapKit and CoreLocation. Use when working with Map views, annotations, markers, polylines, user location tracking, geocoding, reverse geocoding, search/autocomplete, directions and routes, geofencing, region monitoring, CLLocationUpdate async streams, or location authorization flows. Also use when working with maps, coordinates, addresses, places, directions, distance calculations, or location-based features in Swift apps.
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。
Frontend development guidelines for React/TypeScript applications. Modern patterns including Suspense, lazy loading, useSuspenseQuery, file organization with features directory, MUI v7 styling, TanStack Router, performance optimization, and TypeScript best practices. Use when creating components, pages, features, fetching data, styling, routing, or working with frontend code.
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。
Provides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. Use when discovering interpretable features, analyzing superposition, or studying monosemantic representations in language models.
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。
Turns untargeted LC-MS/MS features (m/z, RT, MS/MS) into confidence-stratified metabolite annotations using spectral-library matching (matchms), in-silico tools (SIRIUS/CSI:FingerID, MetFrag) and molecular networking, and assigns a defensible MSI/Schymanski confidence level to each. Use when naming detected features, scoring MS/MS against a reference library, running SIRIUS, or deciding what confidence level an evidence set actually supports. For upstream feature extraction see metabolomics/xcms-preprocessing and metabolomics/msdial-preprocessing; for downstream enrichment that must respect these levels see metabolomics/pathway-mapping; for lipid-specific structural annotation see metabolomics/lipidomics.
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。
ZMK Firmware (オープンソースキーボードファームウェア) リファレンス。 Getting Started (hardware, user-setup, customization, zmk-cli)、 Features (bluetooth, split keyboards, encoders, displays, lighting, pointing, studio, low-power)、 Keymaps (keycodes, modifiers, combos, conditional layers)、 Behaviors (タップ・ホールド、レイヤー、マクロ、tap-dance, sticky-key)、 Input Processors、Hardware Integration、Troubleshooting (building, flashing, connection, hardware issues)。
Feature-Sliced Design (FSD、フロントエンドアーキテクチャ手法) リファレンスとルール。 別名: fsd, feature sliced design, feature-sliced。 レイヤー (app / pages / widgets / features / entities / shared)、 依存方向、Public API パターン、スライス、セグメント (ui / model / api / lib / config)。 コードレビュー・リファクタリング時に自動参照。
Hermes Agent CLI リファレンス。 インストール、CLI コマンド (chat, model, gateway, config, skills, cron, webhook, mcp, profile)、 Configuration (Terminal Backends, Memory, TTS / STT, Compression, Display, Auxiliary Models)、 Features (Tools, Skills, MCP, Memory, Voice Mode, Personality, Context Files)、 Messaging Gateway (14+ プラットフォーム)、Security、Architecture、 Platform Support、Nous Portal 連携 (Tool Gateway)。
TanStack Table (React Table) v9 ヘッドレステーブル (@tanstack/react-table) の API リファレンス。 ark-ui / chakra-ui のスタイル付き Table とは別。 useTable, tableFeatures, createColumnHelper, flexRender, createCoreRowModel, sorting, column / global / fuzzy filtering, faceting, pagination, row selection, expanding, grouping / aggregation, column / row の ordering・pinning・sizing・visibility, virtualization。 v8 legacy (useReactTable / getCoreRowModel) と v9 移行。
有馬記念分析システムのアーキテクチャ/レイヤー境界レビュー。docs/ARCHITECTURE.md のレイヤー構成（commands / domain / repositories / models / features / constants / database / utils / types）に対し、レイヤーディレクトリの意味と配置、参照系(queries)と更新系(aggregates)の分離、DB 接続の注入可能性とテスト容易性、リッチドメインモデルの維持（commands 肥大・ドメイン貧血症）、重み・閾値の constants 単一定義、ファイル配置と命名語彙の一致、不要な抽象化、種別分岐のポリモーフィズム化、生成引数の凝集（5個以上は分割シグナル）を検証。純粋性・依存方向の逆流・DB 接続の生成箇所は lint が error で担保するため扱わない。Use when user says 'アーキテクチャレビュー', 'レイヤー境界チェック', 'review architecture', or '依存方向の確認'.
Parses, queries, converts, and extracts from GTF and GFF3 gene-model annotation files - walking the gene/transcript/exon/CDS hierarchy with gffutils (queryable SQLite DB), converting formats and extracting transcript/CDS/protein FASTA with gffread, slurping to dataframes with gtfparse/pyranges, and sanitizing malformed files with AGAT. Covers the 1-based-inclusive vs 0-based BED coordinate conversion (start-1 only), deriving implicit features (introns/UTRs/TSS), phase-not-frame, the stop-codon-in-or-out-of-CDS convention, and the chr1-vs-1 seqid and gene-ID-version mismatches that silently produce all-zero count matrices and dropped joins. Use when extracting features or sequences from an annotation, converting GTF<->GFF3 or GTF->BED, traversing the gene tree, or diagnosing a coordinate/provenance mismatch upstream of counting or DE.
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。
Planner→Builder→EvaluatorのLong-Runningエージェントハーネスで複雑なタスクを実装します。plannerがfeatures.jsonに機能を分解し、builderがTDDで1機能ずつ実装し、evaluatorがPASSするまでbuilderを繰り返します。「〇〇を作って」「実装して」「long-running」などのリクエストで起動します。