6,626 件 ・ 関連度順
概要と使いどころ
Adds new WebSocket event subscriptions to OneKey. Use when implementing new socket events, handling server push messages, or adding real-time data subscriptions. Socket, WebSocket, event, subscription, push, real-time.
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Rust のコードを書く・直す・レビューするときに使う。所有権、借用、Clone/Copy derive、文字列型 (`String`, `&str`, `Cow`, `'static str`) の選び方を、安易な複製や過剰な lifetime 固定に寄せず、実際のデータ所有者と呼び出し境界に合わせて判断するためのスキル。
Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization.
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 implementing, refactoring, or extending the internal table runtime inside this repository. Covers the current architecture layers, state model, composable flow, where different responsibilities live, how to add features cleanly, and what kinds of refactors are encouraged.
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。
根据指定的行切片规则和列映射，将源DataFrame（df_sub）的列数据转换为长格式DataFrame，包含sub_id、trial、start_time、end_time等字段。
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 the user asks to 'plan my day', 'help me plan today', 'morning planning', 'what should I work on today', 'daily planner', 'evening reflection', 'reflect on my day', 'migrate tasks', 'carry tasks forward', 'rapid log', 'brain dump my tasks', or mentions ADHD-friendly planning, time-blindness, swim lanes, energy-based task management, bullet journal for ADHD, or dopamine menu. Provides a BuJo-style daily planning system with swim lanes, migration, reflection, and dopamine rewards. Part of the ADHD-founder.com ecosystem.
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。
Time-blind friendly planning, executive function support, and daily structure for ADHD brains. Specializes in realistic time estimation, dopamine-aware task design, and building systems that actually work for neurodivergent minds.
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。
Control a running TouchDesigner instance via twozero MCP — create operators, set parameters, wire connections, execute Python, build real-time visuals. 36 native tools.
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。
Builds real-time features. SignalR hubs, SSE (.NET 10), JSON-RPC 2.0, gRPC streaming, scaling.
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。
Complete guide for TUnit advanced applications. Use when using TUnit for data-driven testing, dependency injection, or integration testing. Covers MethodDataSource, ClassDataSource, Matrix Tests, Properties filtering. Includes Retry/Timeout control, WebApplicationFactory integration, Testcontainers multi-service orchestration. Keywords: TUnit advanced, TUnit advanced, MethodDataSource, ClassDataSource, Matrix Tests, MatrixDataSource, MicrosoftDependencyInjectionDataSource, Property, Retry, Timeout, data-driven testing, test filtering, WebApplicationFactory TUnit, multi-container orchestration
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。
Complete guide for upgrading xUnit 2.9.x to 3.x. Use when upgrading xUnit v2 to v3 or understanding xUnit v3 new features and breaking changes. Covers package updates, async void fixes, IAsyncLifetime adjustments. Includes new features: Assert.Skip, Explicit Tests, Matrix Theory, Assembly Fixtures. Keywords: xunit upgrade, xunit v3, xunit 3.x, xunit migration, xunit upgrade, xunit.v3, OutputType Exe, IAsyncLifetime v3, Assert.Skip, SkipUnless, SkipWhen, Explicit attribute, MatrixTheoryData, AssemblyFixture, breaking changes
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。
Complete guide for AutoFixture advanced customization techniques. Use when you need to customize AutoFixture builders or handle special type test data generation rules. Covers DataAnnotations automatic integration, ISpecimenBuilder implementation, priority management. Includes DateTime/numeric range builders, generic design, and fluent extension methods. Keywords: autofixture customization, autofixture customize, autofixture customization, specimen builder, ISpecimenBuilder, RandomDateTimeSequenceGenerator, NumericRangeBuilder, DataAnnotations autofixture, fixture.Customizations, Insert(0), custom builder, NoSpecimen, generic builder
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。
Sync shared repo assets into local ~/.github and ~/.codex, and apply MCP settings from the shared canonical runtime catalog.
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。
Detect and exploit race condition vulnerabilities in web applications using Turbo Intruder's single-packet attack technique to bypass rate limits, duplicate transactions, and exploit time-of-check-to-time-of-use flaws.
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。
Detects and prevents code injection attacks targeting serverless functions (AWS Lambda, Azure Functions, Google Cloud Functions) through event source poisoning, malicious layer injection, runtime command execution, and IAM privilege escalation via function modification. The analyst combines static analysis of function code, CloudTrail event correlation, runtime behavior monitoring, and IAM policy auditing to identify injection vectors across the expanded serverless attack surface including API Gateway, S3, SQS, DynamoDB Streams, and CloudWatch event triggers. Activates for requests involving Lambda security assessment, serverless injection detection, function event poisoning analysis, or serverless privilege escalation investigation.
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。
Detects ransomware encryption activity in real time using entropy analysis, file system I/O monitoring, and behavioral heuristics. Identifies mass file modification patterns, abnormal entropy spikes in written data, and suspicious process behavior characteristic of ransomware encryption routines. Activates for requests involving ransomware behavioral detection, entropy-based file monitoring, I/O anomaly detection, or real-time encryption activity alerting.
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。
Detect unauthorized modifications to running containers by monitoring for binary execution drift, file system changes, and configuration deviations from the original container image.
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 teaches security teams how to deploy and operationalize Amazon GuardDuty for continuous threat detection across AWS accounts and workloads. It covers enabling protection plans for S3, EKS, EC2 runtime monitoring, and Lambda, interpreting finding severity levels, and building automated response workflows using EventBridge and Lambda.
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。
Builds SOC performance metrics and KPI tracking dashboards measuring Mean Time to Detect (MTTD), Mean Time to Respond (MTTR), alert quality ratios, analyst productivity, and detection coverage using SIEM data. Use when SOC leadership needs operational visibility, continuous improvement tracking, or executive-level reporting on security operations effectiveness.
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。
Parse Windows Prefetch files to determine program execution history including run counts, timestamps, and referenced files for forensic investigation.
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。
Builds real-time incident response dashboards in Splunk, Elastic, or Grafana to provide SOC analysts and leadership with situational awareness during active incidents, tracking affected systems, containment status, IOC spread, and response timeline. Use when IR teams need unified visibility during incident coordination and post-incident reporting.
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。
Investigate compromised Docker containers by analyzing images, layers, volumes, logs, and runtime artifacts to identify malicious activity and evidence.
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。
Investigate and triage runtime incidents involving the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration in AEM as a Cloud Service environments only, using runtime-backed MCP evidence.
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。
Analyze and improve Core Web Vitals, load times, and runtime performance.
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。