「troubleshoot」の検索結果

Generates and updates secure, production-ready Kubernetes YAML manifests optimized for GKE Autopilot and GKE Standard clusters. Use when creating or modifying GKE deployment manifests, configuring container security contexts, setting CPU/memory resource limits, defining readiness/liveness/startup probes, mounting secrets and volumes, configuring GKE Gateway API routes, targeting Spot VMs, or deploying AI model inference workloads (vLLM, TGI, Gemma). Don't use for live cluster operations, pod troubleshooting (use gke-workload-troubleshooting), or cluster infrastructure provisioning (use gke-cluster-creation).

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Monitors and troubleshoots GKE TPU workloads, nodes, and node pools using GKE system metrics and PromQL. Use when monitoring TensorCore duty cycle, TPU memory, node readiness, multi-host TPU node pool availability, host maintenance or preemption interruptions, and calculating MTTR or MTBI metrics for GKE TPUs. Don't use for general non-TPU GKE workload monitoring or non-metric TPU debugging.

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Configure and troubleshoot Google Cloud cross-project centralized logging and read-time aggregation. Use when: - Setting up log routing from multiple projects/folders/organizations to a central log bucket. - Creating cross-project log sinks and configuring central log buckets. - Troubleshooting cross-project routing. Don't use for single-project basic configurations.

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Diagnoses GKE JobSet interruptions, restarts, and preemptions for AI/ML training workloads autonomously. Use when troubleshooting JobSet restart loops, spot VM preemptions, node readiness failures, host VM issues, or coordinator worker crashes. Don't use for general GKE cluster creation, basic workload deployment, or non-JobSet application issues.

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Provides data-retrieval best practices, tool selection guidance, and performant SQL query syntax for BigQuery telemetry across INFORMATION_SCHEMA, Cloud Monitoring, and the REST API. Use when the telemetry to fetch is already known, selecting telemetry tools, writing performant INFORMATION_SCHEMA queries, retrieving telemetry for diagnosing single-job performance bottlenecks, investigating slot contention, job concurrency and queue latency, analyzing reservation capacity, utilization and autoscaling saturation, or auditing capacity-based and on-demand compute and storage resource billable usage. Don't use for root-cause diagnosis or symptom troubleshooting when the cause is unknown (use bigquery-troubleshooting first), or for writing or optimizing business logic SQL (use bigquery-optimization).

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Troubleshoots Google Cloud Gemini Enterprise Agent Platform issues (Agent Gateway, Registry, Identity, Policies, Model Armor, Identity-Aware Proxy (IAP)). Use when agent requests fail with 403 (especially unauthorized egress), Agent Runtime queries return 500, or gateway/IAP logs show permission errors. Don't use for general Google Cloud Identity and Access Management (IAM) debugging or networking issues unrelated to the Agent Platform stack.

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Use when a practitioner needs to classify the risk level of an upcoming Salesforce deployment, define rollback trigger conditions, or assign decision authority before the release window opens. Triggers: 'how risky is this release', 'what needs rollback planning', 'classify deployment risk', 'pre-deployment risk checklist', 'rollback decision authority', 'high risk metadata types'. NOT for executing the deployment itself, writing CI/CD pipeline code, or troubleshooting failures after a deployment has already run — use admin/change-management-and-deployment for execution planning and devops/deployment-error-troubleshooting for post-failure diagnosis.

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Use when designing, reviewing, or troubleshooting Salesforce connected apps, External Client Apps, Named Credentials, External Credentials, and OAuth-based integration access. Triggers: 'connected app', 'OAuth flow', 'client credentials', 'JWT bearer', 'Named Credential', 'External Credential', 'integration user', 'IP restrictions', 'connectedApp-meta.xml', 'ExternalClientApplication', 'ExtlClntAppOauthSettings', 'isAdminApproved', 'refreshTokenPolicy', 'ipRelaxation', 'consumer key', 'consumer secret', 'permittedUsersPolicyType'. NOT for OAuth error codes you are already seeing — use admin/connected-app-troubleshooting. NOT for External Credential principal-type setup steps — use integration/named-credentials-setup.

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Expert debugger for Next.js + Cloudflare Workers + Supabase stacks. Systematic troubleshooting for auth, caching, workers, RLS, CORS, and build issues. Activate on: 'debug', 'not working', 'error', 'broken', '500', '401', '403', 'cache issue', 'RLS', 'CORS'. NOT for: feature development (use language skills), architecture design (use system-architect).

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Assesses the patient’s ability to troubleshoot insulin pump malfunctions such as occlusion, battery failure, or error messages. Trigger phrases include “Review pump alarm responses” and “Ensure patient knows steps for pump error”.

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Guides AI agents through Senzing entity resolution workflows using the Senzing MCP server. Covers data mapping to Senzing format, SDK code generation (Python, Java, C#, Rust, TypeScript/Node.js), documentation search, error troubleshooting, sample data access, reporting and visualization, SDK setup guides, and V3-to-V4 migration. Use when working with entity resolution, record matching, record linkage, deduplication, Senzing SDK integration, data mapping for Senzing ingestion, or troubleshooting Senzing error codes. Also use when the user mentions matching records across data sources, finding duplicate entities, identity resolution, master data management, or needs to resolve who is who across datasets.

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Read-only first troubleshooting workflow for Python project deployments, including systemd startup failures, dependency issues, encoding problems, permissions, proxy setup, and readiness gates.

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ネットワーク品質を総合的に診断し、ボトルネックの特定と根本原因の深堀りまで行うスキル。 接続情報、レイテンシ、ダウンロード速度、HTTP接続タイミング、経路解析を自動実行し、 品質閾値に基づく総合評価を日本語レポートとして出力する。 外部依存なし（OS標準ツールのみ使用）、macOSおよびLinux対応。 Use when diagnosing network quality, troubleshooting slow connections, identifying network bottlenecks, measuring latency/bandwidth/jitter, or generating network health reports. 「ネットワーク診断」「network diagnostics」「ネットワークが遅い」 「latency check」「bandwidth test」「traceroute analysis」

システムログを分析してエラーの根本原因を特定し、段階的に深堀りしていくデバッグ専門家スキル。 アプリケーションログ、システムログ、クラウドサービスログなど様々な形式に対応。 5 Whys、タイムライン分析、Fishbone分析などのRCA（根本原因分析）手法を用いて 問題の本質を突き止め、再発防止策まで提案する。 Use when analyzing system logs to find error root causes, debugging application issues, or performing technical post-mortem analysis with log data. For organizational incident management processes (post-incident review, corrective action plans, incident reports without log data), use incident-rca-specialist instead. Triggers: "analyze this log", "find the root cause", "debug this error", "why is this failing", "log analysis", "what caused this crash", "troubleshoot this issue"

METAINFORMANT rules for directory projects/hymenoptera_amalgkit/doc/04_troubleshooting. 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.

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Expert en documentation d'agents IA (README, API docs, exemples d'usage, troubleshooting, changelog)

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Expert DevOps troubleshooter specializing in rapid incident response, advanced debugging, and modern observability.

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Comprehensive guide for installing, configuring, operating, and troubleshooting OpenClaw — a self-hosted, multi-channel AI agent gateway. Use when the user asks about OpenClaw setup, configuration, channel management (WhatsApp/Telegram/Discord/Slack/iMessage/etc.), model provider setup, Gateway operations, multi-agent routing, security hardening, troubleshooting, or any maintenance task related to their local OpenClaw installation. Also use when encountering errors from `openclaw` CLI commands or the Gateway daemon.

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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)。

Motion アニメーションライブラリ (旧 Framer Motion) リファレンス。 React コンポーネント motion, AnimatePresence, AnimateView, LayoutGroup, LazyMotion, MotionConfig, Reorder。hooks useAnimate, useScroll, useSpring, useTransform, useMotionValue, useInView。 vanilla JS API animate, scroll, inView, hover, press, stagger, spring, timeline, motionValue。Vue 版 (motion-v) v-motion ディレクティブ, useScroll 等の composable, Motion+ 限定コンポーネント (Carousel, Cursor, Ticker, Typewriter, AnimateNumber)。transitions / layout / drag / gestures / SVG / scroll アニメーション、accessibility, performance, bundle 最適化, troubleshooting。

NVIDIA DGX Spark User Guide リファレンス。GB10 Grace Blackwell Superchip ハードウェア仕様、first-boot / UEFI 設定、Spark Stacking クラスタ、 DGX OS / NGC / container runtime ソフトウェアスタック、 PXE / cloud-init プロビジョニング、fleet lifecycle 運用、 apt / fwupdmgr 更新、system recovery、PSIRT サポート、 vLLM / TensorRT-LLM / Ollama / ComfyUI / NIM / NeMo fine-tune / NCCL 等の build.nvidia.com/spark playbook、複数 Spark 接続・Tailscale・VS Code、 NVIDIA Developer Forums 由来の known issues / troubleshooting。

Claude Code (code.claude.com) の CLI 本体リファレンス。 CLAUDE.md memory, settings.json, env-vars, model config, keybindings, statusline, terminal config, cli-reference (-p / --continue / --resume), sessions, checkpointing, worktrees, remote control, channels, deep links, troubleshooting。

This skill should be used when the user wants to "investigate a bug", "debug an issue", "figure out why something is happening", "find the root cause", "troubleshoot", "強い推論で調査", "仮説を立てて検証", "原因を特定", "バグの原因調査", "なぜ動かないか調べて", "問題を切り分け", "原因不明", "デバッグ", or mentions systematic hypothesis-driven debugging. NOTE: Use this for investigating UNKNOWN causes, not for validating design proposals (use devils-advocate for that).

Generates troubleshooting guides and FAQ sections for PHP projects. Creates problem-solution documentation.

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。