152 个 ・ 集成工具: Datadog · 按人气排序
Use for 'why does X work this way', 'why we picked Y', design rationale, regressions, postmortems, or data-backed thresholds. Discovers available MCPs and queries each evidence category (source control, issue tracker, long-form docs, real-time chat, infrastructure observability, error tracking, product analytics warehouse) in parallel, then returns a cited read on decisions and tradeoffs. Use how for runtime behavior.
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实现日志 / 指标 / 追踪三大支柱时使用。覆盖 OpenTelemetry / Prometheus / Grafana / Jaeger / Datadog / Sentry 集成。融合 Google SRE 三支柱 + 结构化日志 + Trace Context 传播。
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配置监控和告警时使用。适用于 Prometheus / Grafana / Loki / PagerDuty / SLO 定义 / 告警规则设计。融合 Google SRE 四大黄金信号 + USE Method + 告警分级。
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Measure Mycelium's own scaffold token cost (CLAUDE.md + engine + harness + canvas + memory) and surface a structured estimate. One-shot audit; pair with /framework-health for trend tracking.
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Assess delivery health metrics. For software: DORA + APEX. For content/AI/service products: product-type-appropriate metrics.
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Design and implement multi-stage CI/CD pipelines using GitHub Actions with matrix builds, dependency caching, artifact management, and secret handling. Create workflows that span linting, testing, building, and deployment stages with parallel execution and conditional logic. Use when setting up automated testing and deployment for a new project, migrating from Jenkins or CircleCI to GitHub Actions, implementing matrix builds across platforms, adding build caching, or creating multi-stage pipelines with security scanning and quality gates.
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AI-assisted debugging specialist with deep knowledge of modern debugging tools, observability platforms, and automated root cause analysis. Implements Cursor Debug Mode methodology — structured hypothesis ranking, targeted code instrumentation, human-in-the-loop reproduction gate, log-confirmed root cause, and mandatory cleanup.
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Use when a SaaS founder is deciding on or building a product-led growth motion — assessing PLG readiness, choosing freemium vs free trial vs reverse trial, defining activation and PQLs, designing self-serve onboarding and conversion triggers, building viral loops, or setting up PLG metrics (NRG, activation rate, TTV, NDR, CAC payback) and cohort analysis. Also for hybrid product-led-sales design and PLG-vs-sales-led GTM decisions. Not for paid acquisition channel mix (use channel-expert) or the mechanics of price points and tiers (use pricing).
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Datadog provider for obz. Supports metrics (Datadog Query Language), logs (Datadog Log Query), and traces. Requires api-key and app-key configured under auth in config.yaml. Does not support metric labels, label-values, or series commands. This skill should be used when the user mentions "Datadog", "DD", "obz -p dd", Datadog Query Language, or needs to configure Datadog provider instances with regional endpoints.
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Multi-backend observability CLI for querying metrics, logs, and traces across 12 backends. This skill should be used when the user runs obz commands, constructs metric/log/trace queries, configures providers, parses obz JSON output, or troubleshoots obz errors. Covers all core commands (metric query/list/info/labels/label-values/series, log search, trace search/get), global flags, time formats, output modes, config files, and exit codes.
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Use when the user asks about supply-chain attacks, third-party / vendor compromise (SolarWinds, Kaseya, 3CX, MOVEit, XZ-utils-style), software-bill-of-materials risks, or library / dependency-injection attacks. Self-updating knowledge cell.
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Datadog guidance — APM, logs, metrics, monitors, SLOs, dashboards, and cost control on the Datadog platform.
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Use when a task needs senior data-scientist judgment — designing or reading out an experiment, investigating a metric move, deciding whether a causal claim holds, or judging whether a model or analysis actually supports the decision it's being used for.
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Set up application observability with Prometheus, Grafana, Datadog, or CloudWatch — instrument metrics endpoints, configure Golden Signal dashboards, define alert rules with burn-rate SLOs, and add structured logging
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Use when monitoring Agentforce agent sessions, analyzing conversation logs, measuring deflection rates, or diagnosing agent performance issues. Triggers: 'agentforce session analytics', 'how to query agent conversation data', 'monitor agentforce agent effectiveness', 'agent deflection rate', 'utterance analysis agentforce'. NOT for Trust Layer audit logging — use agentforce/einstein-trust-layer. NOT for designing the topic boundaries and guardrails that cause the misrouting you are seeing in the data — use agentforce/agentforce-guardrails.
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Detects missing or incomplete PrivacyInfo.xcprivacy privacy manifest files, enforcing Guideline 5.1 and Apple's required-reason API declaration policy enforced from May 1, 2024.
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Datadog CLI for searching logs, querying metrics, tracing requests, and managing dashboards. Use this when debugging production issues or working with Datadog observability.
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Query and filter Datadog logs from the shell using the Composio CLI. Run scoped log searches, pivot across services/environments, and export structured JSON for incident investigation and diagnostics.
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Use when building Grafana dashboards backed by Prometheus, Loki, or Tempo, designing PromQL/LogQL queries, wiring template variables, setting alert rules, building SLO dashboards, or maintaining dashboards as code. Triggers: rate() vs increase() confusion, irate vs rate, label_replace, recording rules, alerting rule expressions, multi-dimensional template variables, ad-hoc filters, dashboard JSON model, provisioning via Terraform/grafonnet, p99 / histogram_quantile usage. NOT for Datadog/New Relic dashboards (vendor-specific), Grafana plugin development, or Loki ingestion pipeline tuning.
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Implementing distributed tracing with W3C Trace Context — the byte-precise `traceparent` and `tracestate` header formats, OpenTelemetry's W3CTraceContextPropagator as the modern default (replacing X-B3-* and X-Datadog-*), head vs tail sampling, and HTTP→SQL trace propagation via sqlcommenter. Grounded in the W3C REC and OpenTelemetry specs.
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Comprehensive backend development guide for Langfuse's Next.js 14/tRPC/Express/TypeScript monorepo. Use when creating tRPC routers, public API endpoints, BullMQ queue processors, services, or working with tRPC procedures, Next.js API routes, Prisma database access, ClickHouse analytics queries, Redis queues, OpenTelemetry instrumentation, Zod v4 validation, env.mjs configuration, tenant isolation patterns, or async patterns. Covers layered architecture (tRPC procedures → services, queue processors → services), dual database system (PostgreSQL + ClickHouse), projectId filtering for multi-tenant isolation, traceException error handling, observability patterns, and testing strategies (Jest for web, vitest for worker).
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Optimize end-to-end application performance with profiling, observability, and backend/frontend tuning. Use when coordinating performance optimization across the stack.
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Fluxo de trabalho de infraestrutura em nuvem e DevOps abrangendo AWS, Azure, GCP, Kubernetes, Terraform, CI/CD, monitoramento e desenvolvimento nativo em nuvem.
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CLI do Datadog para buscar logs, consultar métricas, rastrear requisições e gerenciar dashboards. Use isso ao depurar problemas em produção ou trabalhar com observabilidade do Datadog.
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