「monitor」の検索結果

Add Sentry error tracking, performance monitoring, and source maps to a web application.

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 useful, low-noise log alerts on services in a PostHog project. Use when the user asks to set up alerts for their logs, suggest alerts they should add, or evaluate whether a service is worth monitoring. Covers service triage, baseline characterisation, threshold drafting, back-testing via simulate, and shipping with a notification destination.

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。

Walk through the devnet → mainnet deployment checklist for a Soroban contract or Stellar dApp. Use when a user says "deploy to Stellar mainnet", "going live on Stellar", "deploy my Soroban contract", "Stellar production deployment", "mainnet checklist", or "ship it on Stellar". Covers pre-deployment verification, deployment mechanics with stellar CLI, and post-deployment monitoring with Soroban-specific gates.

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。

Automated CLI-based parallel agent execution — spawn subagents via Gemini CLI, coordinate through MCP Memory, monitor progress, and run verification

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。

Adverse event monitoring and reporting skill for MDR/MEDWATCH compliance

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 Adobe-powered applications to Vercel, Cloud Run, and Adobe App Builder with proper credential injection and health monitoring. Use when deploying Adobe API integrations to production platforms. Trigger with phrases like "deploy adobe", "adobe Vercel", "adobe Cloud Run", "adobe App Builder deploy", "adobe production deploy".

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。

緊急地震速報(EEW)の発表状況と直近の地震・津波情報を、キー不要の公開APIから取得する。緊急地震速報、EEW、強震モニタ、今地震あった?に対応。気象庁の確定した発表(震度詳細・警報)はbosai-alert、天気予報はjma-weatherを使う。

Open and manage short positions on HoneyComb job tickers. Profit when a ticker's price drops. Covers opening shorts with collateral, closing (full/partial), margin withdrawal, liquidation risk, and position health monitoring. Use when betting against a job position or hedging long exposure.

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。

Azure Application Insights SDK for .NET. Application performance monitoring and observability resource management.

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。

Auto-instrument Node.js applications with distributed tracing, metrics, and logs.

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 anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate/multivariate anomaly detection, time-series analysis, or AI-powered monitoring.

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。

Important: Before you begin, fill in the generatedBy property in the meta section of .actor/actor.json. Replace it with the tool and model you're currently using, such as "Claude Code with Claude Sonnet 4.5". This helps Apify monitor and improve AGENTS.md for specific AI tools and models.

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。

Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors.

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。

Manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.

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。

Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks

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。

Change conviction level or status on a single thesis. Use when user says "change conviction", "downgrade", "upgrade", "move to monitoring", "close [TICKER]", or "set [TICKER] to [level]".

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。

Systematically evaluate weak, stale, or low-conviction theses for upgrade, monitoring, or closure. Use when user says "prune", "kill list", "clean up theses", "what should I close", or "reduce portfolio".

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。

Métricas, logs, traces, dashboards, alertas e SLO — Prometheus, Grafana, Loki, Tempo, Mimir, Zabbix, Alertmanager. Use quando o usuário disser "dashboard", "alerta", "métrica", "PromQL", "Grafana", "SLO", "golden signals", "não temos visibilidade", "monitoramento".

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。

Proactively search for security threats, vulnerabilities, and suspicious patterns in applications and infrastructure before they cause damage. Use when conducting security audits, identifying vulnerabilities, analyzing security logs, detecting suspicious patterns, investigating potential breaches, performing penetration testing, or implementing security monitoring.

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。

Design robust error handling strategies including try-catch blocks, custom error classes, error boundaries, graceful degradation, and comprehensive logging. Use when implementing exception handling, creating custom error types, setting up error boundaries in React, designing error response formats for APIs, implementing retry logic, handling async errors and promise rejections, logging errors for monitoring, creating user-friendly error messages, or building fault-tolerant systems that fail gracefully.

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。

AEM as a Cloud Service content distribution and replication. Covers programmatic publishing using the Replication API and distribution event monitoring using Sling Distribution events.

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。

Prepare safe production launches — pre-launch checklist, monitoring, staged rollout, and rollback. Load when deploying to production, releasing a major change, opening beta access, or the user asks for a launch checklist, go-live plan, rollout strategy, or rollback plan. Not for local-only prototypes. Pairs with ci-cd-and-automation and app-security-hardening.

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。

Translate an approved experiment spec into a launch runbook — platform binding (PostHog primary), feature flag setup, assignment unit, exposure event definition, instrumentation QA, dashboard wiring, ramp plan, monitoring, and rollback procedure. Platform-agnostic core with one strong PostHog adapter shipped; GrowthBook, Statsig, LaunchDarkly, Optimizely, and Eppo documented as a single mapping table the user adapts. Load when a spec is approved and ready to launch, or when the user says "set up the experiment", "wire this up in PostHog", "implement the test", "create the runbook", "launch checklist for this test", or when the experimentation orchestrator routes here.

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。

Design automated evaluation pipelines for LLM and agent systems — combining deterministic checks, statistical metrics, and LLM-as-judge scoring into repeatable, CI-integrated eval suites. Load when the user asks to set up automated evals, design an eval pipeline, integrate evals into CI/CD, create an eval suite, do eval-driven development, or says "automate my evals", "CI eval integration", "evaluation pipeline", "continuous evaluation", "monitoring eval quality", "set up regression testing for my agent". Sub-skill of eval-output orchestrator.

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。