1.7万 件 ・ 関連度順
概要と使いどころ
Use the DBX CLI to inspect DBX-managed database connections, explore schemas, run bounded read-only queries, generate DBML or schema documentation, and open tables in DBX Desktop. Use when the user asks to work with a database configured in DBX from a shell-capable AI agent. Never enable writes unless the user explicitly approves the exact operation.
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。
Write JavaScript or Python for the n8n Custom Code Tool (@n8n/n8n-nodes-langchain.toolCode) — the AI-agent-callable tool, NOT the workflow Code node. Use when building a Code Tool attached to an AI Agent, writing code that an LLM will invoke, parsing the `query` input, returning a string result, defining an input schema for structured arguments (specifyInputSchema, jsonSchemaExample, DynamicStructuredTool), or troubleshooting errors like "Wrong output type returned", "No execution data available", "The response property should be a string, but it is an object", "Cannot assign to read only property 'name'", or an AI agent that refuses to call the tool. Covers the critical differences between Code node and Code Tool: return format (string vs `[{json:{...}}]`), unavailability of `$fromAI`/`$input`/`$helpers` in the Code Tool sandbox, naming rules for AI invocation, and when to use `toolWorkflow`/HTTP Request Tool 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。
Use when refactoring Handsontable code - applying SOLID principles, Law of Demeter, plugin extraction, performance optimization, code modernization, and API redesign with backward compatibility preservation
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 developing or modifying the @handsontable/angular-wrapper package - Angular components with decorators, NgZone performance optimization, and ng-packagr build system
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 developing or modifying the @handsontable/vue3 wrapper package - Vue 3 SFC components, deep watchers, and provide/inject patterns for settings propagation
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 whenever you are about to create, push, open, update, or edit a pull request in the Handsontable monorepo – load this BEFORE running `gh pr create` or pushing a feature/docs/fix branch, not only when the user says "PR". Triggers: create/open/submit a PR, push the branch, commit and push, ship it, ready to review, update or fix a PR description, any PR URL, finishing work on a `feature/*`/`docs/*`/`fix/*` branch, or a completed ClickUp/DEV task ready to submit. Covers branch naming, pre-flight lint/tests, the PR-first then changelog flow, `gh auth` fallback, and filling the GitHub PR template.
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 adding user-facing text to Handsontable, creating new language constants, updating translation files, or working with RTL layouts and internationalization
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 creating a demo or test page for manual testing of Handsontable. Trigger when the user asks to create a demo, test page, repro page, reproduction case, manual test, or wants to verify a bug fix or feature visually. Also trigger when the user mentions dev-generated.html, dev-pr.html, dev-latest.html, dev.html, or wants to compare behavior between a released version and a local build. Use this for any PR that needs a manual testing artifact.
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, fixing, or reviewing tests for any Handsontable change (unit, E2E, or wrapper), and whenever a test is red during feature work. Enforces that tests prove intended behavior – not just execute code, and never "green for the sake of green". Covers intent-first (write the test from the requirement, ideally before the code), deciding whether the code or the test is wrong when red (default: the code), the banned ways of faking green, write-the-failing-test-first, verify-with-a-real-run, no hollow assertions, not mocking the unit under test, and migrating broken legacy tests.
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 testing a local or public URL on a real device via BrowserStack, opening a live browser session on Android, iOS, or desktop browsers, or when the user mentions BrowserStack, real device testing, mobile testing, cross-browser testing, touch testing, or wants to verify behavior on a specific phone, tablet, or browser version. Also trigger when the user says "test this on Android/iPhone/Safari/Chrome mobile", asks to open a live session, or mentions demo-mobile.html, even if they don't mention BrowserStack by name.
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 visual regression tests or adding a demo route for one - covers the decision rule (what earns a capture, and that a visual spec is in addition to a Playwright assertion), the custom tablePage fixture, the screenshot workflow, reg-suit comparison, and the demo routes in examples/next/visual-tests/
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 creating or modifying any .mjs file in the Handsontable monorepo - scripts, utilities, or library modules. Covers .mjs conventions, native node: imports, top-level await, cross-platform compatibility, and fs/promises async patterns. Trigger on any new .mjs file creation, not just files in scripts/ directories.
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 GKE Cloud TPU multi-slice training hangs (Megascale `HANG_DETECTED` logs and hang monitored events) using the ML Diagnostics `Megascale XLA (MXLA) Hang Analyzer` (`gcloud alpha mldiagnostics monitored-events`) and 1-minute Cloud Monitoring multi-slice latency metrics (`kubernetes.io/container/multislice/*`). Distinguishes XLA compiler/HLO launch divergence and host data-input stalls from TPU chip, SparseCore, ICI, or network fabric faults. Use when multi-slice TPU training jobs freeze without progressing steps, emit `HANG_DETECTED`, or stall in collective operations. Don't use for gradual step-time throughput drops without hangs (use gke-ai-troubleshooting-tpu-performance-degradation) or pod preemption/eviction restarts (use gke-ai-troubleshooting-jobset-interruption).
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 GKE Cloud TPU training throughput drops and step-time regressions (15%+ TPU duty-cycle drop) using ML Diagnostics Workload Monitoring (`gcloud alpha mldiagnostics monitored-events` / `hypercomputecluster.googleapis.com/v1alpha`) and 1-minute Cloud Monitoring system metrics (`kubernetes.io/node/accelerator/*`). Distinguishes hardware and network fabric throttling from workload resource bottlenecks (HBM capacity, host memory, or host CPU saturation). Use when TPU training throughput or duty cycle drops without crashing pods, when `PERFORMANCE_DEGRADATION` monitored events fire, or when triaging slow multi-slice training steps. Don't use for complete multi-slice XLA execution stalls with `HANG_DETECTED` logs (use gke-ai-troubleshooting-tpu-mxla-hang) or pod eviction/interruption restarts (use gke-ai-troubleshooting-jobset-interruption).
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。
Monitors, troubleshoots, and manages GKE TPU Dynamic Slices custom resources. Use when checking TPU slice lifecycle states, troubleshooting slice provisioning failures, validating single-slice or multi-slice (JobSet) workload manifests, or safely patching stuck finalizers and disabling the slice controller. Don't use for generic GKE cluster node pool creation or standard non-TPU workload management (use gke-basics or gke-cluster-creation 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。
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。
Deploy open models or custom weights from Model Garden to Agent Platform endpoints, check the status of an in-progress deployment operation, or clean up resources by undeploying models and deleting endpoints. Use when asked to actively deploy a model, list the Model Garden CATALOG of available models, check if a specific model is deployable (`gcloud ai model-garden models list-deployment-config`), query deployment cost, troubleshoot deployment errors (like quota limits), or undeploy/clean up endpoints. Also use when copying and deploying a 1P Tuned Model. Don't use for pure listing/discovery questions of the form "is X deployed?", "list my endpoints", or "which regions have models running?" — for those use `agent-platform-endpoint-management`. Don't use for running model evaluations (use `agent-platform-eval-flywheel` 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。
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).
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 and manage trusted local Paseo plugins. Use when the user asks to create, edit, install, reload, enable, disable, remove, or troubleshoot a Paseo plugin; add lifecycle hooks; transform agent configuration, environment, MCP servers, or workspace creation; automate permissions or turn follow-ups; add a screen, sidebar header or footer item, or workspace panel; add Command Center items or slash commands; add composer pills or attachment sources; transform, render, or append agent timeline items; contribute a theme; use Paseo from plugin code; or add plugin RPCs.
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。
Hourly warehouse health sweep for {{warehouse_schema}}. Checks every monitored table's freshness against its SLA, compares row counts to the table's own trailing baseline, diffs the schema for drift, and checks for failed or stalled loads. Posts anomalies to {{alert_channel}} and drafts a GitHub issue in {{incident_repo}} with the likely cause. Read-only across the warehouse — never modifies data, tables, or 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。
Free domain research and availability checking. No API keys or credentials required. Uses RDAP (1195+ TLDs) with whois CLI fallback for universal coverage. Checks if domains are available, searches keywords across TLDs, performs WHOIS/RDAP lookups, checks expiry dates, and finds nameservers. Use when the agent needs to: check if a domain is available, search for domains, find who owns a domain, check domain expiration, get nameservers, bulk check domains, or do any domain research. Triggers on: 'check domain', 'is domain available', 'search domains', 'domain availability', 'who owns this domain', 'whois', 'domain expiry', 'when does domain expire', 'nameservers for', 'domain research', 'find domains for', 'domain ideas', 'bulk domain check'.
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。
Linux networking expert for iptables, nftables, routing, DNS, and network 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。
Turn a Wren project's context layer into a shareable, browser-side GenBI web app and deploy it to the user's Vercel or Cloudflare account. Orchestrates the full flow: `wren genbi build` returns a project-hydrated build instruction, the agent authors the app from scratch into apps/<name>/, then register → verify → deploy produce a shareable URL. Use this skill whenever the user wants to: build a dashboard from their Wren project, make a shareable analytics app, deploy their context layer as a web app, host a GenBI app on Vercel or Cloudflare Pages, or asks for a 'genbi app'.
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。
Operate FrontendIntegration resources and the frontend-forge extension. Use when Codex needs to create a FrontendIntegration from FrontendIntegration YAML, update or patch FI lifecycle state, inspect or troubleshoot FI build output, or create, enable, disable, uninstall, and inspect the frontend-forge extension through its InstallPlan and extension resources.
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。