309 件 ・ 関連度順
概要と使いどころ
Android アプリ開発 (Kotlin) のテストリファレンス。JUnit4, Espresso, テストピラミッド。 テストダブル, Mockito, MockK, Truth, Robolectric, coroutines/Flow/ViewModel テスト。 AndroidJUnit4, ActivityScenario, FragmentScenario, UiAutomator, AndroidTestOrchestrator。 createComposeRule, Compose UI テスト同期。
Generate React Spectrum UI components for Adobe Experience Cloud Shell SPAs and AEM UI Extensions. Provides patterns for pages, forms, data tables, dialogs, and navigation using @adobe/react-spectrum. Guides ExC Shell integration with @adobe/exc-app including runtime.done(), IMS token passthrough, and shell theming. Guides AEM UI Extension development with @adobe/uix-guest for Content Fragment Console, CF Editor, Universal Editor, and Assets View surfaces. Trigger on: building App Builder UI, React Spectrum components, ExC Shell pages, forms, data tables, dialogs, modals, navigation, theming, web-src, Spectrum design system, @adobe/exc-app, AEM extension, AEM UI extension, Content Fragment Console, Universal Editor extension, uix-guest, @adobe/uix-guest, extension points for AEM, customizing AEM surfaces.
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。
Automate Datagma tasks via Rube MCP (Composio). Always search tools first for current schemas.
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。
Generate React Spectrum UI components for Adobe Experience Cloud Shell SPAs and AEM UI Extensions. Provides patterns for pages, forms, data tables, dialogs, and navigation using @adobe/react-spectrum. Guides ExC Shell integration with @adobe/exc-app including runtime.done(), IMS token passthrough, and shell theming. Guides AEM UI Extension development with @adobe/uix-guest for Content Fragment Console, CF Editor, Universal Editor, and Assets View surfaces. Trigger on: building App Builder UI, React Spectrum components, ExC Shell pages, forms, data tables, dialogs, modals, navigation, theming, web-src, Spectrum design system, @adobe/exc-app, AEM extension, AEM UI extension, Content Fragment Console, Universal Editor extension, uix-guest, @adobe/uix-guest, extension points for AEM, customizing AEM surfaces.
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。
メモや文字起こしなどの素材を、読者が理解しやすい順序の記事に組み立てます。導入案や段落の役割を対話で確かめ、合意した文章を別ファイルに保存するスキル。
写真や動画、公開記録の少ない手がかりをつなぎ、場所・日時・組織の関係などを検証します。根拠と仮説を分け、反証や未確認事項も整理する調査スキル。
長期プロジェクトの既存文書を、規則・構造・現状・履歴の役割に整理します。エージェントの参照先と更新ルールを整え、文書のずれや削除したものの再作成を防ぐ運用を支援します。
正解が一つに定まらない判断を、長期的な影響、前提への疑問、実行の現実性、失敗リスクの四つの視点で検討し、反対意見も見える形で推奨案をまとめるスキル。
Caveman at maximum compression: fragments, one word when one word is enough, each fact once. Invoke only with /ultracave or /caveman ultra. Stays on until "stop caveman" or "normal mode".
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。
Three.js shaders - GLSL, ShaderMaterial, uniforms, custom effects. Use when creating custom visual effects, modifying vertices, writing fragment shaders, or extending built-in materials.
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。
Author a HyperFrames slideshow — a presentation, pitch deck, or interactive deck with discrete slides, fragment reveals, branching, hotspot navigation, and built-in presenter mode with speaker notes; also converts an existing page into a deck. Output is a navigable deck, not a rendered MP4. If the user didn't explicitly ask for a slideshow, confirm before authoring. Unclear → /hyperframes.
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。
Supports Gtars for local genomic interval models and set algebra, overlaps and counts, consensus and coverage, tokenization, fragment processing, and refget/BEDbase planning across Python, Rust, and the CLI.
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。
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for image, audio, video, document, and container steganography. Use when the user asks to inspect metadata, alpha or palette channels, LSBs, thumbnails, appended trailers, QR fragments, transcoding artifacts, or recover a hidden payload from media without blind brute force. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
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 Scapy to craft, send, sniff, and dissect TCP/UDP/ICMP/DNS packets, analyze pcap files, implement SYN scans, and detect anomalous traffic such as fragmented or malformed packets. Use when performing authorized network reconnaissance, protocol-level forensic analysis, or building traffic anomaly detection during security 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。
Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is fragm
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。
Generate pragmatic CI/CD pipelines from detected project stack signals — fast baseline generation, repeatable checks, environment-aware deployment stages. Use when setting up CI for a new project, refactoring existing pipelines, or standardizing deployment workflows across multiple repos.
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。
KRACK (CVE-2017-13077..082) and FragAttacks (CVE-2020-24586..588 + 26139-26147) — key reinstallation, fragmentation, and aggregation attacks against WPA2 supplicants. Covers Vanhoef's test scripts, viability against modern patched stacks (mostly mitigated post-2021), residual unpatched embedded devices and IoT vendors, and the practical limitations of these attacks in modern engagements. Use when assessing legacy supplicants, embedded clients, or vendors with poor patch cadence.
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。
Run or plan ATAC-seq QC, alignment, TSS enrichment, fragment-size, blacklist, peak-calling, consensus peak, and differential accessibility workflows.
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 authoring rig specs, agent specs, workflow specs, startup/context fragments, operating-mode declarations, or designing the user spec library. Covers the 4 failure modes (spec instantiates topology but not workflow/mode; spec depends on local paths and fails on another host; agents modify specs as one-off files instead of preserving reusable intent; validation proves YAML shape but not whether topology can run) and the validation-vs-runtime-realization distinction.
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 a restrained particle atmosphere inside one section with configurable shapes, density, gravity, wind, sway, rotation, recycling or settling, pointer disturbance, visibility pausing, responsive limits, and reduced-motion fallbacks. Use for petals, leaves, snow, sparks, confetti, dots, paper, icons, or brand fragments that support a section's mood without obscuring content.
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。
Audits existing tests in any language using formal, research-backed test smell names and the testsmells.org 19-smell academic taxonomy. Use when the caller asks for an academic or citable test-smell review, named smell categories, or a formal severity-ranked smell assessment. Covers Assertion Roulette, Conditional Test Logic, Mystery Guest, Eager Test, Sleepy Test, Unknown Test, Sensitive Equality, and the rest of the catalog across .NET, Python, JavaScript/TypeScript, Java, Go, Ruby, Rust, Swift, Kotlin, PowerShell, and C++. DO NOT USE FOR a quick pragmatic test review (use test-anti-patterns), writing or running tests, framework migration, coverage, or assertion-diversity metrics.
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。
Create or review Blazor components (.razor files) with correct architecture. USE FOR: writing new Blazor components that do NOT involve JavaScript interop, implementing parameters and EventCallback, RenderFragment slots, component lifecycle (OnInitializedAsync, OnParametersSet), async patterns, IAsyncDisposable, CancellationToken, CSS isolation, code-behind. DO NOT USE FOR: creating new projects (use create-blazor-project), JavaScript interop or calling browser APIs from Blazor (use use-js-interop), forms and validation (use collect-user-input), prerendering issues (use support-prerendering), HTTP data fetching patterns (use fetch-and-send-data), coordinating state between unrelated components (use coordinate-components).
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。
Hunting skill for sqli vulnerabilities. Built from 12 public bug bounty reports including modern NoSQL injection (Rocket.Chat CVE-2021-22911 MongoDB $regex, Mongoose ORM CVE-2024-53900 $where bypass), modern ORM raw-fragment SQLi (Django CVE-2024-42005, Sequelize GHSA-wrh9-cjv3-2hpw), second-order SOQL injection (HackerOne Salesforce), time-based blind SQLi in GraphQL resolvers, and SQLi on OIDC-proxy backends. Use when hunting SQLi on any target. Dedicated NoSQL operator injection (MongoDB/CouchDB $where/$regex/$ne) is owned by hunt-nosqli — NoSQL appears here only as adjacent ORM/WAF context.
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。
Predict small-molecule binding poses with DiffDock-L (Corso et al. 2023/2024, github.com/gcorso/DiffDock) — blind diffusion docking that places a ligand into a protein pocket without a predefined search box and ranks the samples with a learned confidence model. Reach for this skill to dock a SMILES or SDF against a PDB, to generate ranked 3D poses for a small fragment library, or to get a starting pose for downstream rescoring. DiffDock predicts geometry, not affinity.
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。