1.7천건 · 관련도순
Parse and analyze Linux auditd logs to detect intrusion indicators including unauthorized file access, privilege escalation, syscall anomalies, and suspicious process execution using ausearch and Python.
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Detect and analyze Linux persistence mechanisms including crontab entries, systemd service units, LD_PRELOAD hijacking, bashrc modifications, and authorized_keys backdoors using auditd and file integrity monitoring
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Performance optimization, profiling, caching strategies, lazy loading, bundle optimization, and monitoring. Use when optimizing application performance, reducing bundle size, implementing caching, or analyzing bottlenecks.
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Watch running terminal processes for crashes and stack traces. When an error appears, navigate to the failing file and line, diagnose, and fix it automatically.
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Debug the signals pipeline locally end-to-end. Covers emitting test signals from fixtures, monitoring Temporal workflows via the REST API, reading sandbox agent logs from object storage, inspecting Docker sandbox containers, and diagnosing common failures (stale ClickHouse embeddings, agentsh network denials, inactivity timeouts). Use when a signal isn't reaching the inbox, a signal-report-summary workflow fails, or a sandbox task run times out.
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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.
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Add Sentry error tracking, performance monitoring, and source maps to a web application.
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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.
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Build AI performance monitoring. TRIGGERS - Use when user needs help with ai-performance-monitor related tasks.
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Build AI crisis monitoring and alerting systems. TRIGGERS - Use when user needs help with ai-crisis-monitor related tasks.
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Build AI compliance monitoring systems. TRIGGERS - Use when user needs help with ai-compliance-monitor related tasks.
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OpenAI API (developers.openai.com) の運用・管理リファレンス。 Administration API, admin API keys, RBAC, roles, groups, invites, projects, spend limits, audit logs, usage / costs API, Terraform provider (openai/openai), workload identity federation (WIF, OIDC / SPIFFE / X.509 / Idira), moderation API, misalignment monitoring, safety alerts / cases, safety best practices, under-18 guidance, ZDR Private Safety Processing (PSP), production best practices, deployment checklist, cost / latency optimization, fast / ultrafast mode, Realtime API costs。 rate limits・error handling・prompt caching・webhooks は openai-api-core、Codex WIF・管理は openai-codex。
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Claude Code (code.claude.com) の権限・セキュリティ・企業管理リファレンス。 permissions (allow / ask / deny), permission modes, auto mode (classifier billing), sandboxing, sandbox environments, sandboxed Bash, zero data retention, data usage, HIPAA, managed settings (MDM / plist / registry), server-managed settings, managedMcpServers, allowedProviders, admin setup, authentication (SSO), network config, corporate launcher, OpenTelemetry monitoring, analytics, costs, large codebases, communications kit / champion kit。
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Wear OS (Kotlin) の androidx.wear API・Watch Face Format (WFF) リファレンス。 Wear Compose の CurvedLayout, rotary input, ambient mode, one-handed gestures, ScalingLazyColumn。 Tiles / Material3TileService / ProtoLayout, ComplicationDataSourceService と ComplicationData 型, Health Services (MeasureClient, ExerciseClient, PassiveMonitoringClient), Data Layer (ChannelClient), WFF の XML 要素・式・コンプリケーションスロット・ユーザー設定・Watch Face Designer。
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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.
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Azure Application Insights SDK for .NET. Application performance monitoring and observability resource management.
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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.
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Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors.
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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
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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".
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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]".
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End-to-end pipeline for writing ML/AI research papers — from experiment design through analysis, drafting, revision, and submission. Covers NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Integrates automated experiment monitoring, statistical analysis, iterative writing, and citation verification.
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Optional vendor skill for Parallel CLI — agent-native web search, extraction, deep research, enrichment, FindAll, and monitoring. Prefer JSON output and non-interactive flows.
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MCP server optimization and transport layer enhancement for claude-flow v3. Implements connection pooling, load balancing, tool registry optimization, and performance monitoring for sub-100ms response times.
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