监控
日志、指标与可观测性
azure-cost-optimization
microsoft
Identify and quantify cost savings across Azure subscriptions by analyzing actual costs, utilization metrics, and generating actionable optimization recommendations. USE FOR: optimize Azure costs, reduce Azure spending, reduce Azure expenses, analyze Azure costs, find cost savings, generate cost optimization report, find orphaned resources, rightsize VMs, cost analysis, reduce waste, Azure spending analysis, find unused resources, optimize Redis costs. DO NOT USE FOR: deploying resources (use azure-deploy), general Azure diagnostics (use azure-diagnostics), security issues (use azure-security)
azure-diagnostics
microsoft
Debug and troubleshoot production issues on Azure. Covers Container Apps diagnostics, log analysis with KQL, health checks, and common issue resolution for image pulls, cold starts, and health probes. USE FOR: debug production issues, troubleshoot container apps, analyze logs with KQL, fix image pull failures, resolve cold start issues, investigate health probe failures, check resource health, view application logs, find root cause of errors DO NOT USE FOR: deploying applications (use azure-deploy), creating new resources (use azure-prepare), setting up monitoring (use azure-observability), cost optimization (use azure-cost-optimization)
x-nets
x-cmd
Enhanced netstat module with cached data and structured output. View network connections, routing tables, and interface statistics in interactive or TSV/CSV formats. Dependency: This is an x-cmd module. Install x-cmd first (see x-cmd skill for installation options). see x-cmd skill for installation.
run-helix-tests
dotnet
"Submit and monitor .NET MAUI unit tests on Helix infrastructure. Supports running XAML, Resizetizer, Core, Essentials, and other unit test projects on distributed Helix queues."
api-error-handling
aj-geddes
Implement comprehensive API error handling with standardized error responses, logging, monitoring, retry logic, and validation patterns. Use when building resilient APIs, debugging issues, improving error reporting, implementing retry logic, handling HTTP error codes, managing API timeouts, designing error response handling, or adding circuit breaker patterns.
Observability
OmniNode-ai
Unified agent observability — action logging, tracking, execution logging, and trace correlation
sd-monitor
platypeeps
Use when the user wants a dated, source-traceable comparison of a watched subject against an explicit baseline, with meaningful deltas and a portable next-state artifact.
atlas-monitoring-observability
kaecer68
"Use when modifying or troubleshooting the Wave 9 observability system (5 detectors), Prometheus metric emission (PR-926 naming convention), /api/llm/health probe path, or wave9 alert rules. Triggers: Wave9Observability, wave9_runtime, atlas_db_init_failures_total, atlas_channel_health_errors_total, /api/llm/health 401, wave9_channel_individual_health, IsAuthFreePath, isPublicPath, MetricDBInitFailures, MetricChannelHealthErrors"
otel-livekit-style
pareelamre
"LiveKit Agents OpenTelemetry style: entrypoint/session lifecycle spans, shutdown callbacks, session metrics, and LLM turn token counters."
money-change
Munyon-Canyon
Checklist for any backend change that moves or records money, including ledgers, shares, swaps, transfers and balances. Use before writing or reviewing code that touches USDC, token amounts, share math, the relayer or Privy signing.
otel-flask-style
pareelamre
"Flask OpenTelemetry style: native FlaskInstrumentor, centralized observability init, Python decorators, OTLP logs, and LLM cost metrics."
otel-fastapi-style
pareelamre
"FastAPI OpenTelemetry style: native FastAPIInstrumentor, centralized observability init, Python decorators, OTLP logs, and LLM cost metrics."
otel-instrument-feature
pareelamre
"Instrument any new feature, endpoint, route, handler, worker, job, CLI command, or user-facing flow with OpenTelemetry spans, metrics, and logs before it lands. Triggers on requests like 'add a new endpoint', 'implement X', 'create a handler for Y', 'build a job to Z', 'add this feature', 'wire up a new route', or any code change that introduces a new business operation."
otel-nextjs-style
pareelamre
"Next.js/Vercel OpenTelemetry style: instrumentation.ts, @vercel/otel bootstrap, native @opentelemetry/api call sites, inline public ingest token, and no raw NodeSDK replacement."
otel-expo-style
pareelamre
"Expo / React Native OpenTelemetry style: bootstrap guards, init ordering, inline public ingest token, mobile-compatible exporters, and product action spans."
python-logging-best-practices
terrylica
Python logging with loguru, structlog, and orjson. TRIGGERS - loguru, structlog, structured logging
otel-supabase-edge-style
pareelamre
"Supabase Edge Function observability style: tiny provider-neutral OTel-shaped shim, OTLP export config, traces/logs/metrics, and LLM cost metrics."
otel-generic-style
pareelamre
"Generic OpenTelemetry style fallback for languages without a dedicated otel-*-style skill (Go, Java/Kotlin, Ruby, Rust, .NET/C#, PHP, Elixir, plain Node, etc.). Native SDK APIs, module-scope tracers/meters, bounded spans, error recording, OTLP logs, and resource attributes."
superlog-onboard
pareelamre
"Onboard a project to Superlog by installing OpenTelemetry traces, logs, and metrics across every app and service in the repo. Triggers on requests like 'install Superlog', 'set up Superlog', 'add Superlog telemetry', 'onboard this repo to Superlog', 'instrument with OpenTelemetry for Superlog'."
dspy
NousResearch
Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming
blogwatcher
NousResearch
Monitor blogs and RSS/Atom feeds for updates using the blogwatcher CLI. Add blogs, scan for new articles, and track what you've read.
blogwatcher
NousResearch
Monitor blogs and RSS/Atom feeds for updates using the blogwatcher-cli tool. Add blogs, scan for new articles, track read status, and filter by category.
hugging-face-trackio
huggingface
Track and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API) or retrieving/analyzing logged metrics (CLI). Supports real-time dashboard visualization, HF Space syncing, and JSON output for automation.
pup
DataDog
Datadog API CLI with 49 command groups, 300+ subcommands. Skills and domain agents for monitoring, logs, APM, security, and infrastructure.