「network」の検索結果

Design a tdmcp feature into an implementable spec before any code is written — choose the layer, define the Zod input schema, lay out the TD network topology, plan the bridge/Python approach, sketch a UI wireframe when relevant, and list probe-first risks + the test plan. Use whenever a tdmcp feature idea needs a design/wireframe/spec, or when someone asks to plan/scope/architect a new tool, generator, effect, control, or AI prompt for the TouchDesigner MCP server.

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Utilizes the TouchDesigner MCP servers (tdmcp and touchdesigner-mcp) to create TOP/CHOP chains, script operators, inspect parameters, and debug node networks.

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 polished, validated architecture, workflow, sequence, data-flow, and lifecycle/state diagrams as explorable standalone HTML with inline SVG, dark/light themes, optional trace motion, and PNG/JPEG/WebP/SVG/WebM export. Accept plain-language requirements or pasted Mermaid flowchart, sequenceDiagram, and stateDiagram input; inspect repository evidence when the diagram must reflect real code. Use when the user asks to visualize system architecture, infrastructure, cloud/security/network topology, technical workflows, API call sequences, request lifecycles, data pipelines, ETL/ELT, data lineage, state machines, or to convert/beautify Mermaid.

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。

Always use when user asks to create, generate, draw, or design a diagram, flowchart, architecture diagram, ER diagram, sequence diagram, class diagram, network diagram, or mentions draw.io, drawio, .drawio files. Use for complex diagrams where Mermaid is insufficient.

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。

Debug iOS apps and profile performance using LLDB, Memory Graph Debugger, and Instruments. Use when diagnosing crashes, memory leaks, retain cycles, main thread hangs, slow rendering, build failures, or when profiling CPU, memory, energy, and network 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。

Implement, review, or improve CloudKit and iCloud sync in iOS/macOS apps. Use when working with CKContainer, CKRecord, CKQuery, CKSubscription, CKSyncEngine, CKShare, NSUbiquitousKeyValueStore, or iCloud Drive file coordination; when syncing SwiftData models via ModelConfiguration with cloudKitDatabase; when handling CKError codes for conflict resolution, network failures, or quota limits; or when checking iCloud account status before performing sync 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。

Build alternative browser engines using BrowserEngineKit. Use when developing a non-WebKit browser engine for iOS in the EU, managing web content rendering processes, configuring GPU and networking processes for browser functionality, checking device eligibility for alternative engines, or working with BrowserEngineKit entitlements.

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。

Measure ad effectiveness with privacy-preserving attribution using AdAttributionKit. Use when registering ad impressions, handling attribution postbacks, updating conversion values, implementing re-engagement attribution, configuring publisher or advertiser apps, or replacing SKAdNetwork with AdAttributionKit for ad measurement.

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。

iOS security best practices including Keychain Services, biometrics, data protection, network security, and App Attest

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。

Manual testing + bug filing for Enterprise / SaaS products. Parses a Feishu test doc (scope + repo + bitable URL), observes staging via claude-in-chrome, captures DOM/console/network/screenshot evidence, then dual-tracks each finding — Feishu Bitable record (with attachments) + GitHub issue (<REPO>#<ISSUE_NUMBER> format — English-primary, Chinese collapsed, R2-hosted screenshots, matching type label). Enforces dedup across bitable + GitHub issues + PRs, and mandatory P0/P1/P2 priority prompt when unclear. Trigger whenever the user says "test and report", "test and report side-by-side", "start system testing", "experience staging", "collaborate on bug filing", "collect feedback", a shared Feishu testing doc, a bitable URL + finding, or any UX/bug needing both bitable + GitHub tracking. Do NOT use for writing product code, PR review, CI debugging, or general "how do I use this product" questions — those go to normal dev / PR-review / support flows.

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。

Workflow automation is the infrastructure that makes AI agents reliable. Without durable execution, a network hiccup during a 10-step payment flow means lost money and angry customers. With it, workflows resume exactly where they left off. This skill covers the platforms (n8n, Temporal, Inngest) and patterns (sequential, parallel, orchestrator-worker) that turn brittle scripts into production-grade automation. Key insight: The platforms make different tradeoffs. n8n optimizes for accessibility

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。

Multiplayer game development principles. Architecture, networking, synchronization.

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 "run pentest commands", "scan with nmap", "use metasploit exploits", "crack passwords with hydra or john", "scan web vulnerabilities with nikto", "enumerate networks", or needs essential penetration testing command references.

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。

Docker containerization expert with deep knowledge of multi-stage builds, image optimization, container security, Docker Compose orchestration, and production deployment patterns. Use PROACTIVELY for Dockerfile optimization, container issues, image size problems, security hardening, networking, and orchestration challenges.

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。

Creating interactive data visualisations using d3.js. This skill should be used when creating custom charts, graphs, network diagrams, geographic visualisations, or any complex SVG-based data visualisation that requires fine-grained control over visual elements, transitions, or interactions. Use this for bespoke visualisations beyond standard charting libraries, whether in React, Vue, Svelte, vanilla JavaScript, or any other environment.

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。

Assess the security posture of Kubernetes etcd clusters by evaluating encryption at rest, TLS configuration, access controls, backup encryption, and network isolation.

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。

Kubernetes penetration testing systematically evaluates cluster security by simulating attacker techniques against the API server, kubelet, etcd, pods, RBAC, network policies, and secrets. Using 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。

TLS 1.3 (RFC 8446) is the latest version of the Transport Layer Security protocol, providing significant improvements over TLS 1.2 in both security and performance. It reduces handshake latency to 1-R

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。

bu skill guides organizations through implementing zero trust architecture in cloud environments following NIST SP 800-207 and Google BeyondCorp principles. It covers identity-centric access controls, micro-segmentation, continuous verification, device trust assessment, and Dağıt:ing Identity-Aware Proxy to eliminate implicit network trust in AWS, Azure, and GCP environments.

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bu skill covers hardening managed Kubernetes clusters on EKS, AKS, and GKE by implementing Pod Security Standards, network policies, workload identity, RBAC scoping, image admission controls, and runtime security monitoring. It addresses cloud-specific security features including IRSA for EKS, Workload Identity for GKE, and Managed Identities for AKS.

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Uses Falco YAML rules for runtime threat Tespit in containers and Kubernetes, monitoring syscalls for shell spawns, file tampering, network anomalies, and privilege escalation. Manages Falco rules via the Falco gRPC API and parses Falco alert output. Use building yaparken container runtime security or investigating k8s cluster compromises.

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。

Tespit etme misconfigured Azure Storage accounts including publicly accessible blob containers, missing encryption settings, overly permissive SAS tokens, disabled logging, and network access violations using Azure CLI, PowerShell, and Microsoft Defender for Storage.

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。

bu skill teaches security teams how to tespit etme
and respond to unauthorized cryptocurrency mining operations in cloud environments. It covers identifying cryptomining indicators through compute usage anomalies, network traffic patterns to mining pools, GuardDuty CryptoCurrency Bul:ings, and runtime process monitoring on EC2, ECS, EKS, and Azure Automation workloads.

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 digital forensics and signal analysis techniques for CTF challenges. Use when analyzing disk images, memory dumps, event logs, network captures, cryptocurrency transactions, steganography, PDF analysis, Windows registry, Volatility, PCAP, Docker images, coredumps, side-c

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。