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Agent Skill · 开发

opentelemetry(OpenTelemetry 命令行)

opentelemetry 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

opentelemetry 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描有提醒项,按安装量在开发类的 21,746 个 Skill 里排第 10,393。

总安装 2,258周安装 96GitHub Stars 26下载 791核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:opentelemetry(OpenTelemetry 命令行)
来源仓库:https://github.com/grafana/skills
仓库路径:skills/opentelemetry
安装命令:
npx skills add https://github.com/grafana/skills --skill opentelemetry
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/grafana/skills --skill opentelemetry

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

用于生成 OpenTelemetry Collector 的配置模板与管道示例。适合对接多种遥测数据源并统一转换为标准 OTLP 格式。支持 Jaeger、Zipkin、Prometheus 等多种接收器与处理器组合。需根据实际网络拓扑调整转发规则与安全传输设置。

注意:采样率设置过高可能导致数据量激增,需平衡成本与精度。

来源仓库内路径:skills/opentelemetry

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/grafana/skills --skill opentelemetry;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

opentelemetry 怎么安装?

在终端执行 npx skills add https://github.com/grafana/skills --skill opentelemetry。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

opentelemetry 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

opentelemetry 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

opentelemetry 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

opentelemetry 用的人多吗?

公开数据是累计安装 2,258 次,近一周安装 96 次,下载 791 次,GitHub 26 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

opentelemetry 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
opentelemetry

OpenTelemetry 命令行 · 本页

2,25826接触敏感数据未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

OpenTelemetry with Grafana

Overview

OpenTelemetry (OTel) is a vendor-neutral framework for collecting observability data (metrics, logs, traces, profiles). Grafana Labs integrates it as a core strategy, offering a full stack to collect, ingest, store, analyze, and visualize telemetry data.

Four-Step Implementation Model

  1. Instrument - Add telemetry using Grafana SDKs, Beyla (eBPF), or upstream OTel SDKs
  2. Pipeline - Build processing infrastructure with Grafana Alloy or OTel Collector
  3. Ingest - Route data to Grafana Cloud OTLP endpoint or self-managed backends
  4. Analyze - Dashboards, alerts, Application Observability, Drilldown apps

Grafana Backends

SignalBackend
MetricsGrafana Mimir
LogsGrafana Loki
TracesGrafana Tempo
ProfilesGrafana Pyroscope

OTLP Endpoint and Authentication

Grafana Cloud OTLP Endpoint

Grafana Cloud exposes a managed OTLP gateway endpoint:

https://otlp-gateway-<region>.grafana.net/otlp

Example regions: prod-us-east-0, prod-eu-west-0, prod-ap-southeast-0

Full example:

https://otlp-gateway-prod-us-east-0.grafana.net/otlp

Authentication - Basic Auth

Grafana Cloud OTLP uses HTTP Basic Auth:

  • Username: Grafana Cloud Instance ID (numeric, e.g. 123456)
  • Password: Grafana Cloud API token (with MetricsPublisher, LogsPublisher, TracesPublisher roles)
Via environment variable (recommended)
# Base64-encode "instanceID:apiToken"
export OTEL_EXPORTER_OTLP_HEADERS="Authorization=Basic $(echo -n '123456:glc_eyJ...' | base64)"
Via Alloy environment variables
export GRAFANA_CLOUD_INSTANCE_ID=123456
export GRAFANA_CLOUD_API_KEY=glc_eyJ...
export GRAFANA_CLOUD_OTLP_ENDPOINT=https://otlp-gateway-prod-us-east-0.grafana.net/otlp

Direct Send (no collector) - Environment Variables

export OTEL_EXPORTER_OTLP_ENDPOINT=https://otlp-gateway-prod-us-east-0.grafana.net/otlp
export OTEL_EXPORTER_OTLP_PROTOCOL=http/protobuf
export OTEL_EXPORTER_OTLP_HEADERS="Authorization=Basic <base64(instanceID:apiToken)>"
export OTEL_RESOURCE_ATTRIBUTES="service.name=myapp,service.namespace=myteam,deployment.environment=production"

Instrumentation by Language

Go

Requirements: Go 1.22+

Install packages:

go get "go.opentelemetry.io/contrib/instrumentation/net/http/otelhttp" \
  "go.opentelemetry.io/contrib/instrumentation/runtime" \
  "go.opentelemetry.io/otel" \
  "go.opentelemetry.io/otel/exporters/otlp/otlpmetric/otlpmetrichttp" \
  "go.opentelemetry.io/otel/exporters/otlp/otlptrace" \
  "go.opentelemetry.io/otel/exporters/otlp/otlptrace/otlptracehttp" \
  "go.opentelemetry.io/otel/sdk" \
  "go.opentelemetry.io/otel/sdk/metric"

Run with environment variables:

OTEL_RESOURCE_ATTRIBUTES="service.name=myapp,service.namespace=myteam,deployment.environment=prod" \
OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317 \
OTEL_EXPORTER_OTLP_HEADERS="Authorization=Basic <base64>" \
go run .

See references/instrumentation.md for full Go code example.


Java (Grafana Distribution - JVM Agent)

Requirements: JDK 8+

Download: grafana-opentelemetry-java.jar from https://github.com/grafana/grafana-opentelemetry-java/releases

Run:

OTEL_RESOURCE_ATTRIBUTES="service.name=shoppingcart,service.namespace=ecommerce,deployment.environment=production" \
OTEL_EXPORTER_OTLP_ENDPOINT=https://otlp-gateway-prod-us-east-0.grafana.net/otlp \
OTEL_EXPORTER_OTLP_PROTOCOL="http/protobuf" \
OTEL_EXPORTER_OTLP_HEADERS="Authorization=Basic <base64>" \
java -javaagent:/path/to/grafana-opentelemetry-java.jar -jar myapp.jar

Optional: Data saver mode (reduces metric cardinality):

export GRAFANA_OTEL_APPLICATION_OBSERVABILITY_METRICS=true

Debug:

export OTEL_JAVAAGENT_DEBUG=true
# Enable console output alongside OTLP
export OTEL_TRACES_EXPORTER=otlp,console
export OTEL_METRICS_EXPORTER=otlp,console
export OTEL_LOGS_EXPORTER=otlp,console

Node.js

Install:

npm install --save @opentelemetry/api
npm install --save @opentelemetry/auto-instrumentations-node

Run:

OTEL_TRACES_EXPORTER="otlp" \
OTEL_METRICS_EXPORTER="otlp" \
OTEL_LOGS_EXPORTER="otlp" \
OTEL_NODE_RESOURCE_DETECTORS="env,host,os" \
OTEL_RESOURCE_ATTRIBUTES="service.name=myapp,service.namespace=myteam,deployment.environment=prod" \
OTEL_EXPORTER_OTLP_ENDPOINT=https://otlp-gateway-prod-us-east-0.grafana.net/otlp \
OTEL_EXPORTER_OTLP_HEADERS="Authorization=Basic <base64>" \
NODE_OPTIONS="--require @opentelemetry/auto-instrumentations-node/register" \
node app.js

Warning: Bundlers like @vercel/ncc can break auto-instrumentation hooks.

See references/instrumentation.md for manual SDK setup example.


Python

Install:

pip install "opentelemetry-distro[otlp]"
opentelemetry-bootstrap -a install

Run:

OTEL_RESOURCE_ATTRIBUTES="service.name=myapp,service.namespace=myteam,deployment.environment=prod" \
OTEL_EXPORTER_OTLP_ENDPOINT=https://otlp-gateway-prod-us-east-0.grafana.net/otlp \
OTEL_EXPORTER_OTLP_PROTOCOL="http/protobuf" \
OTEL_EXPORTER_OTLP_HEADERS="Authorization=Basic <base64>" \
opentelemetry-instrument python app.py

Multi-process servers (Gunicorn, uWSGI): implement post-fork hooks to reinitialize OTel providers per worker.


.NET (Grafana Distribution)

Install NuGet:

dotnet add package Grafana.OpenTelemetry

ASP.NET Core setup:

using Grafana.OpenTelemetry;

var builder = WebApplication.CreateBuilder(args);
builder.Services.AddOpenTelemetry()
    .WithTracing(configure => configure.UseGrafana())
    .WithMetrics(configure => configure.UseGrafana());
builder.Logging.AddOpenTelemetry(options => options.UseGrafana());

Run:

OTEL_RESOURCE_ATTRIBUTES="service.name=myapp,service.namespace=myteam,deployment.environment=prod" \
OTEL_EXPORTER_OTLP_ENDPOINT=https://otlp-gateway-prod-us-east-0.grafana.net/otlp \
OTEL_EXPORTER_OTLP_PROTOCOL="http/protobuf" \
OTEL_EXPORTER_OTLP_HEADERS="Authorization=Basic <base64>" \
dotnet run

Requirements:.NET 6+ or.NET Framework 4.6.2+

See references/instrumentation.md for full.NET examples.


Beyla (eBPF - Language Agnostic)

Grafana Beyla instruments at the network layer - no code changes required, works with any language.

# Docker
docker run --rm -it \
  --privileged \
  -e BEYLA_SERVICE_NAME=myapp \
  -e OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317 \
  -v /sys/kernel/security:/sys/kernel/security \
  grafana/beyla

Verify with: curl http://localhost:9090/metrics

Full docs: https://grafana.com/docs/beyla/


Grafana Alloy Collector

Grafana Alloy is the recommended OTel Collector distribution. It combines upstream OTel Collector components with Prometheus exporters for infrastructure + application observability correlation.

Why Use a Collector?

  • Cost control: Aggregate, sample, and drop data before sending
  • Reliability: Buffer and retry on connection failures
  • Enrichment: Add resource attributes, transform, redact, and route data

Alloy Ports

PortProtocolPurpose
4317gRPCOTLP gRPC receiver
4318HTTPOTLP HTTP/protobuf receiver

Application -> Alloy -> Grafana Cloud

Application env vars (point to local Alloy):

export OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317
export OTEL_EXPORTER_OTLP_PROTOCOL=grpc

Alloy config env vars (Alloy -> Grafana Cloud):

export GRAFANA_CLOUD_OTLP_ENDPOINT=https://otlp-gateway-prod-us-east-0.grafana.net/otlp
export GRAFANA_CLOUD_INSTANCE_ID=123456
export GRAFANA_CLOUD_API_KEY=glc_eyJ...

See references/collector-config.md for full Alloy configuration.


Kubernetes Setup

Option 1: Grafana Kubernetes Monitoring Helm Chart (recommended)

The Grafana Kubernetes Monitoring Helm chart deploys Alloy with OTLP receivers pre-configured.

  1. Enable "OTLP Receivers" in the Cluster Configuration tab
  2. Get gRPC/HTTP endpoints from "Configure Application Instrumentation" section
  3. Point apps to the in-cluster Alloy endpoint:
export OTEL_EXPORTER_OTLP_ENDPOINT=<GRPC_ENDPOINT_FROM_HELM>
export OTEL_EXPORTER_OTLP_PROTOCOL=grpc

Option 2: OpenTelemetry Operator

Install via official docs, then use Instrumentation CR for auto-injection:

apiVersion: opentelemetry.io/v1alpha1
kind: Instrumentation
metadata:
  name: my-instrumentation
spec:
  exporter:
    endpoint: http://otelcol:4317
  propagators:
    - tracecontext
    - baggage
  java:
    # Use Grafana distribution image
    image: us-docker.pkg.dev/grafanalabs-global/docker-grafana-opentelemetry-java-prod/grafana-opentelemetry-java:2.3.0-beta.1
  nodejs: {}
  python: {}

Inject into pods with annotation:

metadata:
  annotations:
    instrumentation.opentelemetry.io/inject-java: "true"
    # or: inject-nodejs, inject-python, inject-dotnet

See references/collector-config.md for Kubernetes Alloy Helm values and OTel Collector YAML.


Sampling Strategies

Head-Based Sampling

Decision made at trace start - low overhead, may miss rare errors.

Environment variable (probability sampler):

export OTEL_TRACES_SAMPLER=parentbased_traceidratio
export OTEL_TRACES_SAMPLER_ARG=0.1   # 10% of traces

Alloy head sampling config:

otelcol.processor.probabilistic_sampler "default" {
  sampling_percentage = 10
  output {
    traces = [otelcol.exporter.otlphttp.grafana_cloud.input]
  }
}

Tail-Based Sampling

Decision made after all spans collected - can sample based on outcome (e.g. keep all errors).

Alloy tail sampling config:

otelcol.processor.tail_sampling "default" {
  decision_wait            = "10s"
  num_traces               = 100000
  expected_new_traces_per_sec = 10

  policy {
    name = "keep-errors"
    type = "status_code"
    status_code {
      status_codes = ["ERROR"]
    }
  }

  policy {
    name = "probabilistic-sample"
    type = "probabilistic"
    probabilistic {
      sampling_percentage = 10
    }
  }

  output {
    traces = [otelcol.exporter.otlphttp.grafana_cloud.input]
  }
}

Key Environment Variables Reference

VariableDescriptionExample
OTEL_EXPORTER_OTLP_ENDPOINTOTLP receiver URLhttps://otlp-gateway-prod-us-east-0.grafana.net/otlp
OTEL_EXPORTER_OTLP_PROTOCOLTransport protocolgrpc or http/protobuf
OTEL_EXPORTER_OTLP_HEADERSAuth headersAuthorization=Basic <base64>
OTEL_RESOURCE_ATTRIBUTESService metadataservice.name=myapp,service.namespace=team,deployment.environment=prod
OTEL_TRACES_EXPORTERTrace exporter typeotlp
OTEL_METRICS_EXPORTERMetrics exporter typeotlp
OTEL_LOGS_EXPORTERLogs exporter typeotlp
OTEL_SERVICE_NAMEService name (shorthand)myapp
OTEL_TRACES_SAMPLERSampler typeparentbased_traceidratio
OTEL_TRACES_SAMPLER_ARGSampler argument0.1 (10%)

Key Resource Attributes

AttributePurposeExample
service.nameService identifiershoppingcart
service.namespaceGroups related servicesecommerce
deployment.environmentEnvironment tierproduction, staging
service.versionApp version1.2.3

Useful Links

平台分布

Codex

36.59%
按下载量换算289

Claude

29.86%
按下载量换算236

Cursor

16.65%
按下载量换算132

Gemini CLI

9.16%
按下载量换算72

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

可疑

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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