「offline」の検索結果

Use for authorized hardware and embedded interface security research including UART/JTAG discovery, debug pad triage, secure boot overview, and offline firmware extraction support.

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 for an incident response plan, IRP, escalation matrix or incident playbook. Writes an offline HTML plan with severities, escalation contacts and comms; DR restores service, IRP runs the incident.

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。

Validates defensive controls with paired authorized action and observation evidence, distinguishing blocked, prevented, detected, responded, and telemetry-gap outcomes. Use for purple-team validation design or offline fixture review; not unsanctioned testing or production efficacy claims.

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。

Conducts hypothesis-driven, evidence-preserving threat hunts with bounded negative conclusions and telemetry-gap handling. Use for hunt hypotheses, scoped offline analysis, or analytic follow-up; not unscoped scanning, malware execution, or generic intelligence summaries.

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。

Validates bounded cybersecurity exercise observations against approved scope, expected behavior, runtime controls, and redacted evidence. Use when performing safe offline validation or authorized runtime checks with explicit stop and status gates.

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 error boundary hierarchy, fallback UI patterns, offline-first fallback, retry mechanisms, and graceful degradation.

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。

Real-time communication patterns for live updates, collaboration, and presence. Use when building chat applications, collaborative tools, live dashboards, or streaming interfaces (LLM responses, metrics). Covers SSE (server-sent events for one-way streams), WebSocket (bidirectional communication), WebRTC (peer-to-peer video/audio), CRDTs (Yjs, Automerge for conflict-free collaboration), presence patterns, offline sync, and scaling strategies. Supports Python, Rust, Go, and TypeScript.

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。

Retrieve arXiv paper metadata with keyword queries or import an offline arXiv export, and save results as JSONL (`papers/papers_raw.jsonl`).

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。

Integrate ManagedCode.Orleans.SignalR for grain-driven SignalR delivery, connection and group routing, offline user queues, and restart-safe state. USE FOR: Orleans backplane setup, grain-to-hub publishing, reconnect, heartbeat, and client-invocation failures. DO NOT USE FOR: ordinary SignalR without Orleans or unrelated persistence. INVOKES: inspect configuration, implement the integration, and validate connected-client delivery.

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 writing Playwright tests, fixing flaky tests, debugging failures, implementing Page Object Model, configuring CI/CD, optimizing performance, mocking APIs, handling authentication or OAuth, testing accessibility (axe-core), file uploads/downloads, date/time mocking, WebSockets, geolocation, permissions, multi-tab/popup flows, mobile/responsive layouts, touch gestures, GraphQL, error handling, offline mode, multi-user collaboration, third-party services (payments, email verification), console error monitoring, global setup/teardown, test annotations (skip, fixme, slow), test tags (@smoke, @fast, @critical, filtering with --grep), project dependencies, security testing (XSS, CSRF, auth), performance budgets (Web Vitals, Lighthouse), iframes, component testing, canvas/WebGL, service workers/PWA, test coverage, i18n/localization, Electron apps, or browser extension testing. Covers E2E, component, API, visual, accessibility, security, Electron, and extension 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。

State-first design pass — inventories and implements all non-happy states (loading, empty, error, partial, conflict, offline) before the happy path, and refactors impossible boolean state to proper state machines. Use when starting a new screen, reviewing an existing one for edge-case gaps, or when the user says "handle the error state" / "add loading states" / "what happens when data is missing". Invoke when the user asks for unhappy on their UI, or mentions 'unhappy' alongside design / UI / frontend work.

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。

Production-readiness pass — audits and implements the full non-happy-path matrix: loading skeletons, empty states, error messages, partial data, i18n, offline, permissions, and first-run guidance. Use when preparing a surface for production or when the user says "it crashes on empty data" / "there's no loading state" / "harden this". Invoke when the user asks for harden on their UI, or mentions 'harden' alongside design / UI / frontend work.

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 to KEGG pathway enrichment for DEG results. Covers ORA vs GSEA, mandatory directionality splitting, KEGG organism codes, API failure handling with offline fallbacks, cross-condition comparisons, and answer-first reporting. Consult when running enrichment with clusterProfiler or gseapy.

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 you need to CAPTURE / PRODUCE XProf (jax.profiler) profiling artifacts from sgl-jax (SGLang on JAX/TPU) for later performance analysis: driving a live server (/start_profile, stage-separated prefill/decode), offline bench_one_batch --profile, or kernel microbench. This skill produces the trace files; it does not analyze them.

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。

Applies client-server architecture for web/mobile apps. Use when designing systems with centralized backend services, trust boundaries, or offline-first sync.

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 when working with Hugging Face Datasets: loading local or Hub datasets, defining Features schemas, processing/streaming datasets, converting formats, sharing to the Hub, managing cache/offline behavior, or using datasets-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。

Use AgileRL for reinforcement learning workflows: classical RL training, evolutionary HPO, evolvable networks, multi-agent PettingZoo training, offline/bandit data, and LLM fine-tuning.

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。

Routes Argos Translate workflows for offline machine translation, package installation, CLI usage, runtime settings, and troubleshooting.

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。

Route AI-Optimizer reinforcement-learning collection tasks across model-based RL, easy-MARL, offline RL, safe command builders, and repository limitations.

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。

OFFLINE FALLBACK for the claude-md-management plugin - prefer that plugin when it is installed. Audit and improve CLAUDE.md files - scan for CLAUDE.md files, evaluate quality against templates, output a report, then make targeted updates. Invoke explicitly (/claude-md-improver) when the plugin is unavailable.

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, edit, replicate, import, and export draw.io diagrams with an offline YAML-first workflow: architecture, network topologies, flowcharts, UML/ER, org charts, Mermaid/CSV conversion, existing .drawio bundles, style presets, themes, and non-publication formula diagrams. For publication figures (paper, thesis, IEEE, camera-ready) use drawio-academic-skills 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。

Fix Gorse 0.5.x recommendation engine silently disabled or degraded due to config incompatibility with 0.4. Use when: (1) Gorse 0.5 recommendations are poor/empty despite having data, (2) collaborative filtering appears disabled even though [recommend.collaborative] section exists, (3) migrating Gorse config from 0.4 to 0.5, (4) old config keys like [recommend.popular], [recommend.neighbors], [recommend.online], [recommend.offline] are being used with Gorse 0.5. Critical: type="mf" must be explicitly set in [recommend.collaborative] or CF is silently disabled (default "none").

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。

Connect this agent to a running Guaardvark (self-hosted AI studio) and check what it can do right now. Use first when the user mentions Guaardvark, asks to generate images/video/music/voice locally, run a Film Crew, train a LoRA, launch a swarm, or when a guaardvark MCP tool is missing or a call fails with "not reachable" / "plugin offline".

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 an offline ASO audit on canonical App Store metadata under `./Store` and surface keyword gaps using Astro MCP. Use after pulling metadata with `asc metadata pull`.

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。