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Agent Skill · 开发

configuring-opentelemetry-dotnet(配置 opentelemetry dotnet)

configuring-opentelemetry-dotnet 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。

configuring-opentelemetry-dotnet 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,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 8,079。

总安装 3,345周安装 138GitHub Stars 1,514下载 1,093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:configuring-opentelemetry-dotnet(配置 opentelemetry dotnet)
来源仓库:https://github.com/dotnet/skills
仓库路径:skills/configuring-opentelemetry-dotnet
安装命令:
npx skills add https://github.com/dotnet/skills --skill configuring-opentelemetry-dotnet
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/dotnet/skills --skill configuring-opentelemetry-dotnet

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。

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。适合围绕仓库状态、代码变更或协作事项进行整理。可结合来源仓库进一步核验具体用法和适用条件。configuring-opentelemetry-dotnet 属于开发类 Skill,可作为该场景下的辅助能力补充。

安装前建议确认权限范围及是否触发联网或命令执行。当前暂无已知稳定性问题,但需人工复核具体实现细节。

来源仓库内路径:skills/configuring-opentelemetry-dotnet

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/dotnet/skills --skill configuring-opentelemetr…;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

configuring-opentelemetry-dotnet 怎么安装?

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

configuring-opentelemetry-dotnet 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。

configuring-opentelemetry-dotnet 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。

configuring-opentelemetry-dotnet 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。

configuring-opentelemetry-dotnet 用的人多吗?

公开数据是累计安装 3,345 次,近一周安装 138 次,下载 1,093 次,GitHub 1,514 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。

configuring-opentelemetry-dotnet 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 来源仓库有 1,514 星,维护活跃度相对可查。

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
configuring-opentelemetry-dotnet

配置 opentelemetry dotnet · 本页

3,3451,514接触敏感数据未明确通过

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

Configuring OpenTelemetry in.NET

When to Use

  • Adding distributed tracing to an ASP.NET Core application
  • Setting up OpenTelemetry exporters (OTLP is the primary protocol; Jaeger accepts OTLP natively; Prometheus OTLP ingestion requires explicit opt-in)
  • Creating custom metrics or trace spans for business operations
  • Troubleshooting distributed trace context propagation across services

When Not to Use

  • The user wants application-level logging only (use ILogger, Serilog)
  • The user is using Application Insights SDK directly (different API)
  • The user needs APM with a commercial vendor's proprietary SDK

Inputs

InputRequiredDescription
ASP.NET Core projectYesThe application to instrument
Observability backendNoWhere to export: OTLP collector, Aspire dashboard, Jaeger (accepts OTLP natively)

Workflow

Step 1: Install the correct packages

There are many OpenTelemetry NuGet packages. Install exactly these:

# Core SDK + ASP.NET Core instrumentation + logging integration
dotnet add package OpenTelemetry.Extensions.Hosting
dotnet add package OpenTelemetry.Instrumentation.AspNetCore
dotnet add package OpenTelemetry.Instrumentation.Http

# Exporter
dotnet add package OpenTelemetry.Exporter.OpenTelemetryProtocol  # OTLP exporter for traces, metrics, AND logs

# Optional — dev/local debugging only (do NOT include in production deployments)
# dotnet add package OpenTelemetry.Exporter.Console

Do NOT install OpenTelemetry alone — you need OpenTelemetry.Extensions.Hosting for proper DI integration.

Optional: additional auto-instrumentation packages

Install only the packages that match the libraries your application uses:

dotnet add package OpenTelemetry.Instrumentation.SqlClient           # SQL Server queries
dotnet add package OpenTelemetry.Instrumentation.EntityFrameworkCore  # EF Core
dotnet add package OpenTelemetry.Instrumentation.GrpcNetClient       # gRPC calls
dotnet add package OpenTelemetry.Instrumentation.Runtime             # GC, thread pool metrics

Step 2: Configure all signals in Program.cs

using OpenTelemetry.Resources;
using OpenTelemetry.Trace;
using OpenTelemetry.Metrics;
using OpenTelemetry.Logs;

var builder = WebApplication.CreateBuilder(args);

builder.Services.AddOpenTelemetry()
    .ConfigureResource(resource => resource
        .AddService(serviceName: builder.Environment.ApplicationName))
    .WithTracing(tracing => tracing
        .AddAspNetCoreInstrumentation(options =>
        {
            // Filter out health check endpoints from traces
            options.Filter = httpContext =>
                !httpContext.Request.Path.StartsWithSegments("/healthz");
        })
        .AddHttpClientInstrumentation(options =>
        {
            options.RecordException = true;
        })
        // Optional: add SQL instrumentation if using SqlClient directly
        // .AddSqlClientInstrumentation(options =>
        // {
        //     options.SetDbStatementForText = true;
        //     options.RecordException = true;
        // })
        // Custom activity sources (must match ActivitySource names in your code)
        .AddSource("MyApp.Orders")
        .AddSource("MyApp.Payments")
        .AddSource("MyApp.Messaging"))
    .WithMetrics(metrics => metrics
        .AddAspNetCoreInstrumentation()
        .AddHttpClientInstrumentation()
        // Optional: .AddRuntimeInstrumentation() for GC and thread pool metrics
        //   (requires OpenTelemetry.Instrumentation.Runtime package)
        // Custom meters (must match Meter names in your code)
        .AddMeter("MyApp.Metrics"))
    .WithLogging(logging =>
    {
        logging.IncludeScopes = true;
        // logging.IncludeFormattedMessage = true;  // Enable if you need the formatted message string in log exports
    })
    // Single OTLP exporter for all signals — reads OTEL_EXPORTER_OTLP_ENDPOINT
    // env var (defaults to http://localhost:4317). Override via environment variable
    // or appsettings.json configuration.
    .UseOtlpExporter();

Step 3: Understanding log–trace correlation

The .WithLogging() call in Step 2 integrates ILogger with OpenTelemetry:

  • Each log entry automatically includes TraceId and SpanId for correlation with traces
  • The service resource from .ConfigureResource() propagates to logs automatically
  • UseOtlpExporter() applies to logs alongside traces and metrics
  • No additional packages or separate SetResourceBuilder call needed

Step 4: Create custom spans (Activities) for business operations

using System.Diagnostics;
using Microsoft.Extensions.Logging;

public class OrderService
{
    // Create an ActivitySource matching what you registered in Step 2
    private static readonly ActivitySource ActivitySource = new("MyApp.Orders");
    private readonly ILogger<OrderService> _logger;

    public OrderService(ILogger<OrderService> logger) => _logger = logger;

    public async Task<Order> ProcessOrderAsync(CreateOrderRequest request)
    {
        // Start a new span
        using var activity = ActivitySource.StartActivity("ProcessOrder");

        // Add attributes (tags) to the span
        activity?.SetTag("order.customer_id", request.CustomerId);
        activity?.SetTag("order.item_count", request.Items.Count);

        try
        {
            // Child span for validation
            using (var validationActivity = ActivitySource.StartActivity("ValidateOrder"))
            {
                await ValidateOrderAsync(request);
                validationActivity?.SetTag("validation.result", "passed");
            }

            // Child span for payment
            using (var paymentActivity = ActivitySource.StartActivity("ProcessPayment",
                ActivityKind.Client))  // Client = outgoing call
            {
                paymentActivity?.SetTag("payment.method", request.PaymentMethod);
                await ProcessPaymentAsync(request);
            }

            var order = new Order { Id = Guid.NewGuid(), CustomerId = request.CustomerId, Status = "Completed" };

            activity?.SetTag("order.status", "completed");
            activity?.SetStatus(ActivityStatusCode.Ok);

            return order;
        }
        catch (Exception ex)
        {
            activity?.SetStatus(ActivityStatusCode.Error, ex.Message);
            // Log via ILogger — OpenTelemetry captures this with trace correlation.
            // Prefer logging over activity.RecordException() as OTel is deprecating
            // span events for exception recording in favor of log-based exceptions.
            _logger.LogError(ex, "Order processing failed for customer {CustomerId}", request.CustomerId);
            throw;
        }
    }
}

Critical: ActivitySource name must match AddSource("...") in configuration. Unmatched sources are silently ignored — this is the #1 debugging issue.

Step 5: Create custom metrics

Use IMeterFactory (injected via DI) to create meters — this ensures proper lifetime management and testability.

using System.Diagnostics;
using System.Diagnostics.Metrics;

public class OrderMetrics
{
    private readonly Counter<long> _ordersProcessed;
    private readonly Histogram<double> _orderProcessingDuration;
    private readonly UpDownCounter<int> _activeOrders;

    public OrderMetrics(IMeterFactory meterFactory)
    {
        // Meter name must match AddMeter("...") in configuration
        var meter = meterFactory.Create("MyApp.Metrics");

        // Counter — use for things that only go up
        _ordersProcessed = meter.CreateCounter<long>(
            "orders.processed", "orders", "Total orders successfully processed");

        // Histogram — use for measuring distributions (latency, sizes)
        _orderProcessingDuration = meter.CreateHistogram<double>(
            "orders.processing_duration", "ms", "Time to process an order");

        // UpDownCounter — use for things that go up AND down
        _activeOrders = meter.CreateUpDownCounter<int>(
            "orders.active", "orders", "Currently processing orders");
    }

    public void RecordOrderProcessed(string region, double durationMs)
    {
        // Tags enable dimensional filtering (by region, status, etc.)
        var tags = new TagList
        {
            { "region", region },
            { "order.type", "standard" }
        };

        _ordersProcessed.Add(1, tags);
        _orderProcessingDuration.Record(durationMs, tags);
    }
}

Register OrderMetrics in DI:

builder.Services.AddSingleton<OrderMetrics>();

Step 6: Configure context propagation for distributed scenarios

Trace context propagation is automatic for HTTP calls when using AddHttpClientInstrumentation(). For non-HTTP scenarios:

using System;
using System.Collections.Generic;
using System.Diagnostics;
using OpenTelemetry.Context.Propagation;

// ActivitySource should be static — register via .AddSource("MyApp.Messaging") in Step 2
private static readonly ActivitySource MessageSource = new("MyApp.Messaging");

// Manual context propagation (e.g., across message queues)
// On the SENDING side:
var propagator = Propagators.DefaultTextMapPropagator;
var activityContext = Activity.Current?.Context ?? default;
var context = new PropagationContext(activityContext, Baggage.Current);
var carrier = new Dictionary<string, string>();

propagator.Inject(context, carrier, (dict, key, value) => dict[key] = value);
// Send carrier dictionary as message headers

// On the RECEIVING side:
var parentContext = propagator.Extract(default, carrier,
    (dict, key) => dict.TryGetValue(key, out var value) ? new[] { value } : Array.Empty<string>());

Baggage.Current = parentContext.Baggage;
using var activity = MessageSource.StartActivity("ProcessMessage",
    ActivityKind.Consumer,
    parentContext.ActivityContext);  // Links to parent trace!

Validation

  • Traces appear in the observability backend (Jaeger, Aspire dashboard, etc.)
  • HTTP requests automatically create spans with correct verb, URL, status code
  • Custom ActivitySource names match AddSource() registrations
  • Custom Meter names match AddMeter() registrations
  • Logs include TraceId and SpanId for correlation
  • Health check endpoints are filtered from traces
  • Exception details appear on error spans

Common Pitfalls

PitfallSolution
ActivitySource.StartActivity returns nullSource name doesn't match any AddSource() — names must match exactly
Traces not appearing in exporterCheck OTLP endpoint: gRPC uses port 4317, HTTP uses 4318
Missing HTTP client spansEnsure AddHttpClientInstrumentation() is registered; it works for both IHttpClientFactory/DI and new HttpClient() (use IHttpClientFactory for lifetime management)
High cardinality tagsDon't use user IDs, request IDs, or UUIDs as metric tags — explodes storage
OTLP gRPC vs HTTP mismatchDefault is gRPC (port 4317); if collector only accepts HTTP, set OtlpExportProtocol.HttpProtobuf
Meter / ActivitySource lifecycleActivitySource should be static; create Meter via IMeterFactory from DI (not new Meter()) for proper lifetime management and testability

平台分布

Codex

40.45%
按下载量换算442

Claude

28.77%
按下载量换算314

Cursor

17.77%
按下载量换算194

Gemini CLI

10.46%
按下载量换算114

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

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。目前只有一个公开来源,建议同时核对源仓库。

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