1,154 件 ・ 関連度順
概要と使いどころ
Use when the user says 'no hallucinations', 'verify APIs', 'reality check', or 'don't invent functions'. Prevents the agent from calling methods, imports, or variables that do not provably exist in the user's installed version.
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 to inspect Sentry issues or events, summarize recent production errors, or pull basic Sentry health data via the Sentry CLI; perform read-only queries using the `sentry` command.
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 working on the JetBrains chat session UI or SessionModel/SessionController — transcript cards, retained Swing lifecycle, session background surfaces, editor-derived styling, adding session events, and session/controller testing with FakeSessionRpcApi.
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。
Expert guide for using n8n-mcp MCP tools effectively. Use when searching for nodes, validating configurations, accessing templates, managing workflows, organizing workflows into folders, managing credentials, auditing instance security, or using any n8n-mcp tool. Provides tool selection guidance, parameter formats, and common patterns. IMPORTANT — Always consult this skill before calling any n8n-mcp tool — it prevents common mistakes like wrong nodeType formats, incorrect parameter structures, and inefficient tool usage. If the user mentions n8n, workflows, nodes, or automation and you have n8n MCP tools available, use this skill first.
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。
Read AI-Trader financial event snapshots and market-intel endpoints. Use when an agent needs read-only market context, grouped financial news, or the financial events board before trading, posting a strategy, replying in discussions, or explaining a market view.
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。
Reconstruct a bounded incident timeline and separate observed events from suspected causes.
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。
Diagnoses GKE workload failures (CrashLoopBackOff, OOMKilled, ImagePullBackOff, Pending, etc.) via logs and events. Use when pods fail to start or crash repeatedly. Don't use for GKE cluster infrastructure provisioning, node pool creation, or non-Kubernetes Google Cloud services.
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。
Expert guidance for proactive threat hunting in Google SecOps. Use when proactively hunting for threats, retroactively analyzing indicators of compromise (IoCs), performing prevalence searches across enterprise events, hunting for MITRE ATT&CK techniques, or detecting behavioral and statistical outliers using UDM queries. Don't use for incoming alert triage (use secops-triage), active incident response and timeline deep-dives on a known breach (use secops-investigate), or detection rule authoring (use secops-detection-engineering).
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, validate, test, and deploy YARA-L 2.0 detection rules and evaluate end-to-end detection coverage gaps in Google SecOps. Use when writing new detection rules, tuning existing rules, validating syntax, testing logic against historical telemetry, or evaluating detection coverage against threat intelligence blogs, CVE disclosures, and Threat Detection Opportunities (TDOs) using synthetic UDM events and long-running coverage analysis. Don't use for alert triage (use secops-triage), deep forensic event reconstruction on infected hosts (use secops-investigate), or case management operations (use secops-cases).
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。
Expert guidance for deep security incident and entity investigations in Google SecOps. Use when investigating cases, analyzing entities (hosts, IPs, domains, hashes, users), extracting and searching UDM events, performing asset and user timeline analysis, and detecting lateral movement across enterprise networks. Don't use for detection rule authoring or YARA-L tuning (use secops-detection-engineering), proactive hypothesis-driven hunting (use secops-hunt), initial alert triage (use secops-triage), or basic case status updates (use secops-cases).
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。
Diagnoses GKE HorizontalPodAutoscaler (HPA) failures — metrics showing as <unknown>, FailedGetResourceMetric / FailedGetScale / FailedComputeMetricsReplicas events, missing Pod resource requests, custom/external metrics-pipeline breakage (FailedGetExternalMetric / FailedGetCustomMetric, unavailable metrics adapter, control-plane firewall blocking the adapter), HPA that won't scale up or down (tolerance / stabilization window / unavailable rate metrics), scale-to/from-zero problems, and slow HPA reaction on large clusters. Use when an HPA isn't scaling a workload as expected or reports metric errors. Don't use for configuring or authoring new HPA/VPA objects or scaling best practices (see the gke-workload-scaling skill), or for Cluster Autoscaler / node-pool sizing.
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。
Automates the end-to-end detection engineering workflow in Google SecOps using MCP tools. Use when fetching threat intelligence from blogs, generating Threat Detection Opportunities (TDOs), simulating attacker behavior with synthetic UDM events, evaluating rule coverage, and deploying gap-closing rules. Don't use for standalone YARA-L 2.0 rule authoring/tuning (use secops-detection-engineering), threat hunting, or SOC 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。
Diagnoses GKE nodes reporting NotReady or Unknown status by inspecting node conditions, events, kubelet/containerd logs, and node metrics, then proposing safe remediations. Use when nodes show NotReady, when the kubelet stops posting node status, or when workloads are evicted or stuck Pending due to node health. Don't use for pod-level application failures (use gke-workload-troubleshooting), autoscaler scale-up/scale-down decisions (use gke-cluster-autoscaler), or non-GKE compute.
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。
Diagnoses and prevents vbar_control_agent segfaults, out-of-memory (OOM) errors, and TPU device initialization failures on TPU v6e nodes in GKE caused by race conditions during TPU device resets or high-frequency metrics polling. Use when troubleshooting vbar_control_agent crashes, memory cgroup OOMs in serial console logs, tpu-device-plugin metrics checksum corruption errors, or custom TPU metrics collection conflicts on GKE TPU v6e nodes. Don't use for general non-TPU container OOM troubleshooting or standard GKE node lifecycle 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。
Manages Google Analytics account and property settings, enables the Analytics Admin API via the Cloud CLI, lists accounts and properties, and manages data streams, custom dimensions, conversion events, and integrations. Use when you need to programmatically configure Google Analytics accounts, provision properties, manage data retention, configure Measurement Protocol secrets, or manage Firebase and Google Ads links.
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。
Guides developers through managing (adding, removing, and clearing) audience members for Google products using the Data Manager API and its associated client libraries. Use this skill when the user wants to upload audience members, remove specific users, or clear/replace an entire audience for Customer Match, mobile device ID audiences, or any other audience use case supported by the Data Manager API. Don't use for uploading events or conversions (use the data-manager-api-event-ingestion skill).
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。
Diagnoses Google Ads account performance issues such as conversion loss (value or volume), low lead flow/volume, and lost impression share (opportunities) due to ad rank, bids, or budgets. Use when troubleshooting sudden performance drops, analyzing campaign impression share metrics, investigating low lead flow, or searching for bidding and budget constraints. Don't use for setting up new campaigns, uploading conversion events directly, or general Google Mobile Ads SDK integration issues (use gma-android-integrate 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。
How to build desktop applications with GPUI Kit, the Rust framework published as the gpui-kit crate (GPUI plus gpui_kit::component, gpui_kit::base, gpui_kit::assets). Use when setting up a gpui-kit app, choosing or using a component (Button, Input, Select, Dialog, Sheet, Tabs, Sidebar, List, DataTable, Tree, Chart, etc.), handling component state, theming, or window overlays, and for GPUI mechanics: actions and keybindings, async tasks, contexts, custom elements, entities, events, focus, global state, layout and styling, ElementId, and tests including UI integration testing. Holds the normative Coding Guides: read them before any architecture, state-ownership, public API, naming, or testing decision. Pairs with the gpui-kit-design-guides skill for the Design Guides.
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 installing or configuring the OpenSearch extension for KubeSphere, which provides distributed search and analytics engine for storing logs, events, auditing, and notification history
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 installing or configuring the WizTelemetry Data Pipeline (vector) extension for KubeSphere, which provides data collection, transformation, and routing for observability data including logs, auditing, events, and notifications
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。
Diagnose Sentry issues without copy-pasting stack traces. Uses the Composio CLI to pull issue details, events, breadcrumbs, and suspect commits, then maps the frames to local source so the agent can propose a fix directly.
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。
Answer "what's breaking" questions from Sentry — find the right org and project, search issues and events with the vocabulary Sentry uses, and report what is actually firing rather than the first hit. Use when the user asks what errors are happening, whether something is stable, what changed since a release, or for any health summary of a service.
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。
Writes and debugs Apex code, builds Lightning Web Components, optimizes SOQL queries, implements triggers, batch jobs, platform events, and integrations on the Salesforce platform. Use when developing Salesforce applications, customizing CRM workflows, managing governor limits, bulk processing, or setting up Salesforce DX and CI/CD pipelines.
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。
Set up an isolated Python environment for SageMaker / AWS work, with the right Python version and current boto3. Use this skill whenever Python code will be executed for a SageMaker deployment, training job, or any AWS automation — including when about to run `pip install`, when about to invoke `boto3`, when creating or activating a virtualenv, or when the user asks to "set up the environment". Never use system Python and never `pip install` into it. Always isolate. This skill prevents the most common failure modes: wrong Python version, dependency conflicts, and stale SDKs.
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。