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blockchain monitoring AI Skills

Discover blockchain monitoring skills, compare source repositories and read the instructions for each workflow.

Categories: blockchain monitoring

Showing 625–648 of 1,010

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GitHub

python-logging

narumiruna

Use when choosing or configuring Python logging, especially deciding between stdlib logging and loguru for apps or CLIs.

GitHub

production-observability

carmentacollective

Use when adding logging, error monitoring, metrics, Sentry, debugging production issues, or improving observability

GitHub

fastapi-observability

Lobbi-Docs

This skill should be used when the user asks to "add logging", "implement metrics", "add tracing", "configure Prometheus", "setup OpenTelemetry", "add health checks", "monitor API", or mentions observability, A...

GitHub

orchestration-debugging

Euda1mon1a

Troubleshoot agent & tool failures in scheduling orchestration. Use when MCP tools fail, agent communication breaks, constraint engines error, or database operations timeout. Provides systematic incident respon...

GitHub

signal-party

Euda1mon1a

Parallel metrics collection using G-6 SIGNAL. Deploy 6 probes to gather metrics from all sources for data-driven decisions.

GitHub

sentry-server

JasonPaff

Enforces project server-side Sentry monitoring conventions when implementing error tracking, performance monitoring, and breadcrumb logging in server actions, facades, middleware, and API routes. This skill ens...

GitHub

running-performance-benchmarks

wolfiesch

Use this skill when running performance benchmarks, measuring API endpoint response times, detecting performance regressions, running load tests, comparing performance before/after changes, analyzing performanc...

GitHub

observability-patterns

mindmorass

Observability patterns for metrics, logs, and traces. Use when implementing monitoring, setting up Prometheus/Grafana, configuring logging pipelines, implementing distributed tracing, or designing alerting syst...

GitHub

metrics-report

kinneyyan

Posts metrics data to a reporting endpoint. Use this when users need to send metrics data that has been collected and stored in temporary files to a reporting API.

GitHub

audit-log-generator

dengineproblem

Эксперт по аудит-логам. Используй для создания систем логирования, compliance требований, структуры логов и мониторинга.

GitHub

langfuse-trace

pkarpovich

Analyze Langfuse trace JSON exports using jq queries. Use when user provides a Langfuse trace file (.json) for analysis, debugging agent behavior, checking token usage, or investigating tool calls. Triggers on...

GitHub

observability-patterns

vanman2024

Comprehensive observability setup patterns for Google ADK agents including logging configuration, Cloud Trace integration, BigQuery Agent Analytics, and third-party observability tools (AgentOps, Phoenix, Weave...

GitHub

observability

cemezgin

Tracing with OpenTelemetry and structured logging with slog. Use when adding observability to services, handlers, or debugging production issues.

GitHub

monitoring

All-The-Vibes

Comprehensive observability strategy including metrics, logs, traces, and alerting. Use when setting up new applications, debugging production issues, performance optimization, SLA/SLO definition, incident resp...

GitHub

sentry-cli

btraut

Use sentry-cli for release management, debug information files/source maps, sending events, and cron monitor check-ins. Use when configuring authentication, verifying CLI setup, uploading debug files, or runnin...

GitHub

cloud-monitoring

liauw-media

Cloud monitoring with Prometheus, Grafana, and cloud-native tools. Use when setting up metrics, alerts, dashboards, or troubleshooting performance issues.

GitHub

sm-orchestrate

lukeslp

Orchestrate multiple dr.eamer.dev services - manage service groups, dependencies, and parallel health checks.

GitHub

codereview-observability

xinbenlv

Review logging, metrics, tracing, and alerting. Ensures systems are observable, debuggable, and operable. Use when reviewing code that adds logging, metrics, or monitoring.

The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.

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