所有 Skills

chrome-extension-development

211testing-qa

Expert guidelines for Chrome extension development with Manifest V3, covering security, performance, and best practices. Use when building browser extensions, creating popup UIs, implementing content scripts, working with Chrome APIs, managing extension permissions, or publishing to Chrome Web Store.

mindrally

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mysql-best-practices

211database

MySQL development best practices for schema design, query optimization, and database administration

mindrally

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assistant-mcp

211agent-workflows

Connect AI coding agents (Claude Code, Cursor, VS Code, OpenAI Codex) to Grafana Cloud via the `mcp-grafana` Model Context Protocol server. Installs the server with `go install`, generates a Grafana service-account token, wires `~/.claude/settings.json` or `~/.cursor/mcp.json` with the `command` + `env` block, runs `--disable-write` for safer read-only sessions, switches to SSE transport for team-shared / VS Code setups, and verifies with `/mcp` + a `list_datasources` round-trip. Use when connecting Claude Code to Grafana, setting up MCP for Grafana, configuring the Grafana MCP server, using Grafana tools in Cursor/VS Code, querying Grafana from an AI agent, sharing the MCP server across a team — even when the user says "give my agent Grafana access", "let Claude see my metrics", or "Cursor + Grafana" without saying "MCP".

grafana

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app-observability

211backend-api

Get RED metrics + service maps + frontend RUM + AI/LLM monitoring out of Grafana Cloud — Application Observability (`traces_spanmetrics_*` from OTel traces, p50/p95/p99 latency, exemplar-to-trace, traces-to-logs / profiles), Frontend Observability with the Faro Web SDK (Core Web Vitals, session replay, `pushError`, React + router integration, `TracingInstrumentation` for browser → backend trace correlation), and AI Observability via OpenLIT (token / cost / latency, GPU, hallucination + toxicity evals). Use when standing up APM for a service, wiring an Alloy OTLP receiver + forwarding to Cloud, instrumenting a React frontend for RUM, debugging why service-map edges are missing, monitoring LLM cost drift, or correlating a frontend error to its backend trace — even when the user says "set up APM", "show service map", "monitor browser perf", "session replay", "RUM SDK", or "watch our OpenAI bill" without naming App / Frontend / AI Observability.

grafana

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infrastructure

211devops-cloud

Ship Kubernetes, host, container, and cloud-provider telemetry into Grafana Cloud — `k8s-monitoring` Helm chart for K8s clusters (metrics + logs + traces + events + cost), Alloy `prometheus.exporter.unix` for Linux hosts, cAdvisor + Docker discovery for containers, and CloudWatch / Azure Monitor / Google Cloud Monitoring datasource setup. Use when onboarding a new cluster or VM fleet to Grafana Cloud, picking the right Helm values for K8s scraping, wiring kube-state-metrics + node-exporter + cAdvisor, alerting on `PodCrashLooping` / node memory / PVC capacity, or pulling AWS / Azure / GCP cloud metrics — even when the user says "monitor my cluster", "send K8s metrics to Grafana", "scrape EC2 metrics", "cluster pod logs", or "install the monitoring helm chart" without naming `k8s-monitoring` or Alloy.

grafana

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database-observability

211database

Set up Grafana Cloud Database Observability for MySQL and PostgreSQL — enables `pg_stat_statements` / Performance Schema, creates a least-privilege monitoring user, configures the `database_observability.postgres` / `database_observability.mysql` Alloy components, ships query samples + visual explain plans + RED metrics + schema details to Grafana Cloud, and correlates slow queries with application traces via `db.statement` / `db.system` OTel attributes. Use when monitoring database performance, diagnosing slow queries, setting up DB observability for RDS / Aurora / Cloud SQL / Azure Database / self-managed instances, correlating DB metrics with APM, or alerting on query latency — even when the user says "my database is slow", "find the slow queries", or "monitor RDS" without saying "observability".

grafana

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fleet-management

211backend-api

Manage a fleet of Grafana Alloy collectors with Fleet Management — author Alloy pipelines once, target them via attribute matchers (`env="production"`, regex `region=~"us-.*"`), push remotely via OpAMP without restarting collectors. Covers pipeline create / update / matcher RPCs, collector attribute API, `remotecfg` bootstrap block (standalone + Helm), pre-deploy `alloy fmt` validation, the local Alloy UI at port 12345 for component health, and post-deploy `REMOTE_CONFIG_STATUS_APPLIED` verification. Use when standing up a Cloud Alloy fleet, pushing a config change to 200 collectors, hunting why one collector shows `REMOTE_CONFIG_STATUS_FAILED`, validating River syntax before saving, or wiring `discovery.kubernetes` → `prometheus.remote_write` — even when the user says "configure Alloy", "remote config the collectors", "push pipeline", "OpAMP", "collector is unhealthy", or "manage agent config centrally" without naming Fleet Management.

grafana

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oklch-skill

210frontend

用于Web项目的OKLCH颜色空间。将hex/rgb/hsl转换为oklch，生成调色板，检查对比度，处理色域边界，并使用Tailwind v4进行主题设置。触发词：oklch、颜色转换、调色板生成、对比度、色域、display p3、设计令牌、色相漂移、色度、深色模式颜色。

jakubkrehel

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accessibility-a11y

208design-ui

遵循 WCAG 指南实施 Web 无障碍（a11y）最佳实践，以创建包容、无障碍的用户界面。

mindrally

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mimir

207devops-cloud

Stand up Grafana Mimir for horizontally scalable, multi-tenant, long-term Prometheus + OTLP metrics storage. Covers monolithic / read-write / microservices deployment, S3 / GCS / Azure / filesystem block storage, Prometheus `remote_write` and OTLP ingestion, multi-tenancy with `X-Scope-OrgID`, ingester replication factor, compactor retention, and per-tenant limits. Use when running Mimir locally or on Kubernetes (Helm `mimir-distributed`), scaling Prometheus past a single node, picking ingest / query / backend split, configuring tenants and ingestion rate, debugging `/ready` 503s or `429 Too Many Requests`, or pointing Grafana at a Mimir datasource — even when the user says "I need long-term Prometheus storage", "scale Prometheus", "multi-tenant metrics backend", "Cortex replacement", "remote_write target", or "store 10M active series" without naming Mimir.

grafana

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beyla

207backend-api

Auto-instrument an application's HTTP / gRPC / DB traffic with Grafana Beyla eBPF — no code changes, no SDK, no restart. Covers requirements (Linux 5.8+ with BTF, CAP_SYS_ADMIN, host PID), language matrix (Go / Java / Python / Ruby / Node / .NET / Rust / C++ / PHP), Docker + Helm + DaemonSet install, port- / process- / Kubernetes-metadata discovery, OTLP traces + Prometheus metrics export, routes decorator (cardinality control), trace sampling, and Grafana Cloud via Alloy. Use when adding observability to a service you can't recompile, instrumenting a closed-source binary, getting RED metrics + spans onto Tempo/Mimir without touching the app, or rolling Beyla as a cluster-wide DaemonSet — even when the user says "zero-code APM", "instrument legacy app", "trace this binary", "eBPF observability", or "no SDK" without naming Beyla.

grafana

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pyroscope

207backend-api

Continuously profile applications with Grafana Pyroscope and read the result as flame graphs. Covers three instrumentation paths — language SDK push (Go / Java / Python / Ruby / Node / .NET / Rust), Alloy eBPF auto-instrumentation (no code change, requires kernel 5.8+ with BTF), and SDK → Alloy receiver — plus ProfileQL queries, profile types (CPU / memory / allocations / goroutines / mutex), Grafana Cloud Profiles endpoint, and Span Profiles trace-to-profile linking. Use when adding profiling to a service, deploying Alloy as a cluster-wide eBPF profiler, hunting CPU / memory hotspots from a flame graph, comparing two profiles to find a regression, or correlating a slow Tempo trace to its profile — even when the user says "find what's burning CPU", "flame graph this app", "continuous profiling", "heap hotspots", or "why is allocation so high" without naming Pyroscope.

grafana

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dashboarding

207devops-cloud

Build, modify, and ship Grafana dashboards as JSON via the HTTP API — panel types (timeseries / stat / gauge / table / heatmap / logs / traces / node-graph), `gridPos` 24-column layout, units, thresholds, template + datasource + chained variables, transformations (`organize` / `calculateField` / `filterByValue`), panel + dashboard links with `${__field.labels.x}` / `${__from}`, and Loki/Prometheus annotations. Use when scripting dashboard creation, writing the dashboard JSON for a new service, adding a `$job` dropdown variable, computing an "Error %" column with a transformation, overlaying deploys as annotations, or pushing a dashboard via `POST /api/dashboards/db` — even when the user says "create a dashboard for this metric", "add a service dropdown", "show errors as percentage", "overlay our deploys", or "export the dashboard JSON" without naming the API or schema. After every API push, verify with the returned `version` plus a GET on the dashboard UID.

grafana

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alerting-irm

205testing-qa

端到端配置 Grafana Alerting、事件响应管理（IRM）和 SLO——配置 Grafana 管理和数据源管理的告警规则、联系点（Slack/PagerDuty/email/webhook）、带层级匹配器的通知策略、静默、静音时段、值班排班和升级链、事件管理集成，以及带多窗口燃烧率告警的 SLO。在配置告警、调试通知路由、设置值班轮换、声明或管理事件、定义 SLO、通过 YAML 或 API 配置告警、为通知策略选择匹配器、构建 PagerDuty/Slack webhook 接收器，或排查告警未触发的原因时使用——即使用户说“有错误就呼我”、“当 X 发生时提醒我”、“将此路由到平台团队”或“设置 SLO”而未明确提及 Alerting 或 IRM。

grafana

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alloy

205devops-cloud

Build a unified telemetry pipeline with Grafana Alloy — one OpenTelemetry-compatible binary that collects metrics, logs, traces, and profiles and ships to Grafana Cloud / Prometheus / Loki / Tempo / Pyroscope. Covers the Alloy config language (blocks, `sys.env`, component refs), `prometheus.scrape` → `remote_write`, `loki.source.file` + `loki.process` → `loki.write`, `otelcol.receiver.otlp` → `otelcol.exporter.otlp`, `pyroscope.scrape`, K8s / Docker / EC2 discovery, relabeling, modules (`import.file/git/http`), clustering, Fleet Management `remotecfg`, the Alloy UI at `:12345`, and `alloy fmt` / `alloy validate`. Use when writing a `config.alloy`, replacing Grafana Agent / OTel Collector, scraping K8s pods, parsing logs, ingesting OTLP, or debugging "Alloy isn't sending anything" — even when the user says "set up the agent", "write me a scrape config", "drop these logs before sending", or "OTel collector config" without naming Alloy.

grafana

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tempo

205devops-cloud

Stand up Grafana Tempo as a cost-efficient distributed-tracing backend that only needs object storage, and write TraceQL queries against it. Covers OTLP + Jaeger + Zipkin ingestion, the distributor → live-store → block-builder → object-storage write path, metrics-generator for RED spanmetrics + service graphs, Helm `tempo-distributed` deployment, multi-tenant `X-Scope-OrgID`, TraceQL span / resource / event scopes, structural operators (`>>`, `<<`), `rate()` + `quantile_over_time` metrics, and the traces-to-logs / metrics / profiles datasource links. Use when deploying Tempo, writing a TraceQL query for slow / errored requests, debugging "no traces showing in Explore", sizing queriers / compactors, configuring S3 / GCS / Azure block storage, or wiring trace ↔ log ↔ profile correlation — even when the user says "tracing backend", "find slow requests", "show me the service graph", "store traces in S3", "Jaeger compatible store", or "what called this span" without naming Tempo.

grafana

获取

loki

204backend-api

Grafana Loki 日志聚合与 LogQL 查询语言。涵盖 LogQL 语法（日志查询、指标查询、标签匹配器、行过滤器、解析器：json/logfmt/pattern/regexp/unpack、标签过滤器、line_format）、Loki 架构、通过 Alloy/Promtail/Fluent Bit 进行日志采集、结构化元数据以及 Logs Drilldown。在编写 LogQL 查询、配置 Loki、排查日志管道或分析日志时使用。

grafana

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nestjs-best-practices

203security

NestJS 最佳实践与架构模式，用于构建生产级应用。在编写、审查或重构 NestJS 代码时，应使用此技能以确保模块、依赖注入、安全性和性能的正确模式。

kadajett

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promql

203backend-api

编写、验证和优化 Prometheus / Grafana Mimir / Grafana Cloud Metrics 的 PromQL。涵盖 `rate` vs `irate` vs `increase`、标签匹配器和正则表达式、`sum / avg / topk / by / without` 聚合、经典和原生 `histogram_quantile`、带除零保护的比率、用于数据过时的 `absent` / `changes`、时间偏移和 `predict_linear`、记录规则命名、SLO + 燃烧速率计算，以及基数排查指南。适用于编写指标查询、修复错误的 p95、构建错误预算告警、调试“查询缓慢”、查找导致基数爆炸的噪声标签，或将仪表盘查询迁移为记录规则——即使用户只说“计算错误率”、“p99 延迟”、“按服务求和”、“为什么这个查询慢”或“什么在填满 Mimir”而未提及 PromQL。

grafana

获取

grafana-oss

203security

配置 Grafana OSS — 通过 YAML 配置仪表盘，设置数据源（Prometheus / Loki / Tempo / Pyroscope），编写带模板变量的仪表盘 JSON，构建面板查询，分配内置角色（Viewer / Editor / Admin / GrafanaAdmin），生成服务账户令牌，编辑 grafana.ini 服务器配置，创建注释，通过配置安装插件，并使用健康检查 curl 验证每一步。适用于构建仪表盘、配置数据源、设置配置 YAML、选择面板类型、编写模板变量、管理用户和角色、在 grafana.ini 中配置 SMTP/OAuth、通过 API 创建注释、排查配置的仪表盘未显示的问题，或在本地运行 Grafana OSS — 即使用户只说“设置 Prometheus 数据源”、“从 git 配置仪表盘”、“创建服务账户”或“在 OSS 中配置 SSO”而未提及“Grafana OSS”。

grafana

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opentelemetry

203backend-api

使用 OpenTelemetry 检测任何应用，并将指标/日志/追踪发送到 Grafana Cloud 或自托管的 Mimir/Loki/Tempo/Pyroscope。涵盖 Go、Java（Grafana JVM 代理）、Python（`opentelemetry-instrument`）、Node.js、.NET（`Grafana.OpenTelemetry`）的 SDK 自动检测，以及 Beyla eBPF 零代码方案；Grafana Cloud OTLP 网关 + 基本认证（实例 ID + API 密钥，base64）；环境变量配置（`OTEL_EXPORTER_OTLP_*`、`OTEL_RESOURCE_ATTRIBUTES`）；Alloy/OTel-Collector 管道；Kubernetes Operator 注入注解；以及头部采样和尾部采样。适用于检测服务、将 OTLP 指向 Grafana Cloud、从 Jaeger/Datadog/New Relic 迁移、选择头部采样与尾部采样，或调试“Explore 中不显示 spans”的场景——即使用户说“自动检测我的 Java 应用”、“发送追踪到 Grafana”、“我该设置哪些环境变量”、“OTLP 端点”或“Operator 注入”而未明确提及 OpenTelemetry。

grafana

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football-data

202backend-api

Football (soccer) data across the world's major leagues — standings, schedules, match stats, xG, transfers, player profiles, head-to-head history, team strength (Elo), and match forecasts. Zero config, no API keys. Covers Premier League, La Liga, Bundesliga, Serie A, Ligue 1, MLS, Champions League, World Cup, Championship, Eredivisie, Primeira Liga, Serie A Brazil, Russian Premier League, Scottish/Belgian/Turkish top flights, European Championship, and more (call get_competitions for the live list). Use when: user asks about football/soccer standings, fixtures, match stats, xG, lineups, player values, transfers, injury news, league tables, daily fixtures, player profiles, head-to-head records, team strength/Elo ratings, or match odds/forecasts. Don't use when: user asks about American football/NFL (use nfl-data), college football (use cfb-data), NBA (use nba-data), WNBA (use wnba-data), college basketball (use cbb-data), NHL (use nhl-data), MLB (use mlb-data), tennis (use tennis-data), golf (use golf-data), cricket (use cricket-data), Formula 1 (use fastf1), or betting odds (use polymarket or kalshi). Don't use for live/real-time scores — data updates post-match. Don't use get_season_leaders or get_missing_players for non-Premier League leagues (they return empty). Don't use get_event_xg for leagues outside the top 5 (EPL, La Liga, Bundesliga, Serie A, Ligue 1).

machina-sports

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langfuse

201research-knowledge

与 Langfuse 交互并访问其文档。当需要 (1) 通过 CLI 以编程方式查询或修改 Langfuse 数据——包括追踪、提示、数据集、评分、会话以及任何其他 API 资源，(2) 查阅 Langfuse 文档、概念、集成指南或 SDK 用法，或 (3) 了解任何 Langfuse 功能的工作原理时使用。此技能涵盖基于 CLI 的 API 访问（通过 npx）和多种文档检索方法。

langfuse

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temporal-developer

198devops-cloud

Develop, debug, and manage Temporal applications across Python, TypeScript, Go, Java, .NET, Ruby, and Rust. Use when the user is building workflows, activities, or workers with a Temporal SDK, debugging issues like non-determinism errors, stuck workflows, or activity retries, using Temporal CLI, Temporal Server, or Temporal Cloud, or working with durable execution concepts like signals, queries, heartbeats, versioning, continue-as-new, child workflows, or saga patterns. Also use when the user mentions "run a Temporal workflow from the CLI", "start a dev server", "run temporal server start-dev", "temporal workflow start", "temporal workflow execute", "temporal workflow signal", "temporal workflow query", "temporal workflow update".

temporalio

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