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Agent Skill · 前端设计

tempo(tempo 搜索)

tempo 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。

tempo 是前端设计类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证为 MIT,第三方扫描已通过,按安装量在前端设计类的 10,216 个 Skill 里排第 3,877。

总安装 1,077周安装 44GitHub Stars 61下载 348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
MIT

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:tempo(tempo 搜索)
来源仓库:https://github.com/julianobarbosa/claude-code-skills
仓库路径:skills/tempo
安装命令:
npx skills add https://github.com/julianobarbosa/claude-code-skills --skill tempo
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/julianobarbosa/claude-code-skills --skill tempo

这个 Skill 是做什么的

前端设计类 Skill 关注页面结构、视觉规范和组件写法,输出通常是可运行的界面代码。

tempo 用于处理 GitHub 仓库、Issue、Pull Request 等协作信息,辅助代码变更管理。适用于围绕仓库状态和协作事项进行整理与跟踪。通过 npx skills add 命令从指定 GitHub 仓库安装并使用该技能。安装前需确认权限范围和维护状态,避免触发网络请求或文件修改。

tempo 属于前端设计类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/tempo

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/julianobarbosa/claude-code-skills --skill temp…;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

    它需要调用外部服务,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

tempo 怎么安装?

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

tempo 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。

tempo 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

tempo 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

tempo 用的人多吗?

公开数据是累计安装 1,077 次,近一周安装 44 次,下载 348 次,GitHub 61 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。

tempo 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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 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。
  • 需要处理前端设计类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

前端设计类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
frontend-design

前端设计 · Codex、Claude

8,823,360126,072只读MIT通过
vercel-composition-patterns

Vercel 组合模式 · Codex、Claude

3,858,81625,893需要联网MIT通过
vercel-react-native-skills

Vercel React native skills 前端 · Codex、Claude

2,468,66425,878只读MIT通过
adapt

adapt 搜索 · Codex、Claude

2,027,04023,125操作浏览器未明确通过
bolder

bolder 分析 · Codex、Claude

2,004,28823,130只读未明确通过
tempo

tempo 搜索 · 本页

1,07761调用外部服务MIT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

Grafana Tempo Skill

Comprehensive guide for Grafana Tempo - the cost-effective, high-scale distributed tracing backend designed for OpenTelemetry.

What is Tempo?

Tempo is a high-scale distributed tracing backend that:

  • Trace-ID lookup model - No indexing of every attribute, keeps ingestion fast and storage costs low
  • OpenTelemetry native - First-class support for OTLP protocol
  • Object storage backed - Stores traces in affordable S3, GCS, or Azure Blob Storage
  • TraceQL query language - Powerful query language inspired by PromQL and LogQL
  • Apache Parquet format - 5-10x less data pulled per query vs legacy formats
  • Multi-tenant by default - Built-in tenant isolation via X-Scope-OrgID header

Architecture Overview

Core Components

ComponentPurpose
DistributorEntry point for trace data, routes to ingesters via consistent hash ring
IngesterBuffers traces in memory, creates Parquet blocks, flushes to storage
Query FrontendQuery orchestration, shards blockID space, coordinates queriers
QuerierLocates traces in ingesters or storage using bloom filters
CompactorCompresses blocks, deduplicates data, manages retention
Metrics GeneratorOptional: derives metrics from traces

Data Flow

Write Path:

Applications → Collector → Distributor → Ingester → Object Storage
                                  ↓
                           Consistent Hash Ring
                           (routes by traceID)

Read Path:

Query Request → Query Frontend → Queriers → Ingesters (recent data)
                      ↓                            ↓
                 Block Sharding          Object Storage (historical data)
                      ↓                            ↓
              Parallel Querier Work      Bloom Filters + Indexes

Deployment Modes

1. Monolithic Mode (-target=all)

  • All components in single process
  • Best for: Local testing, small-scale deployments
  • Cannot horizontally scale component count
  • Scale by increasing replicas

2. Scalable Monolithic (-target=scalable-single-binary)

  • All components in one process with horizontal scaling
  • Each instance runs all components
  • Good for development with scaling needs

3. Microservices Mode (Distributed) - Recommended for Production

# Using tempo-distributed Helm chart
distributor:
  replicas: 3

ingester:
  replicas: 3

querier:
  replicas: 2

queryFrontend:
  replicas: 2

compactor:
  replicas: 1

Helm Deployment

Add Repository

helm repo add grafana https://grafana.github.io/helm-charts
helm repo update

Install Distributed Tempo

helm install tempo grafana/tempo-distributed \
  --namespace monitoring \
  --values values.yaml

Production Values Example

# Storage configuration
storage:
  trace:
    backend: azure  # or s3, gcs
    azure:
      container_name: tempo-traces
      storage_account_name: mystorageaccount
      use_federated_token: true  # Workload Identity

# Distributor
distributor:
  replicas: 3
  resources:
    requests:
      cpu: 500m
      memory: 2Gi
    limits:
      memory: 4Gi

# Ingester
ingester:
  replicas: 3
  resources:
    requests:
      cpu: 1000m
      memory: 2Gi
    limits:
      memory: 8Gi  # Spikes to 8GB periodically
  persistence:
    enabled: true
    size: 20Gi

# Querier
querier:
  replicas: 2
  resources:
    requests:
      cpu: 100m
      memory: 256Mi
    limits:
      memory: 4Gi

# Query Frontend
queryFrontend:
  replicas: 2
  resources:
    requests:
      cpu: 100m
      memory: 100Mi
    limits:
      memory: 2Gi

# Compactor
compactor:
  replicas: 1
  resources:
    requests:
      cpu: 500m
      memory: 2Gi
    limits:
      memory: 6Gi

# Block retention
compactor:
  compaction:
    block_retention: 336h  # 14 days

# Gateway for external access
gateway:
  enabled: true
  replicas: 1

# Metrics Generator (optional)
metricsGenerator:
  enabled: false

Storage Configuration

Azure Blob Storage (Recommended for Azure)

storage:
  trace:
    backend: azure
    azure:
      container_name: tempo-traces
      storage_account_name: <storage-account-name>
      # Option 1: Workload Identity (Recommended)
      use_federated_token: true
      # Option 2: User-Assigned Managed Identity
      use_managed_identity: true
      user_assigned_id: <identity-client-id>
      # Option 3: Account Key (Dev only)
      # storage_account_key: <account-key>
      endpoint_suffix: blob.core.windows.net
      hedge_requests_at: 400ms
      hedge_requests_up_to: 2

AWS S3

storage:
  trace:
    backend: s3
    s3:
      bucket: my-tempo-bucket
      region: us-east-1
      endpoint: s3.us-east-1.amazonaws.com
      # Use IAM roles or access keys
      access_key: <access-key>
      secret_key: <secret-key>

Google Cloud Storage

storage:
  trace:
    backend: gcs
    gcs:
      bucket_name: my-tempo-bucket
      # Uses Workload Identity or service account

TraceQL Query Language

Basic Queries

# Simplest query - all spans
{ }

# Filter by service
{ resource.service.name = "frontend" }

# Filter by operation
{ span:name = "GET /api/orders" }

# Filter by status
{ span:status = error }

# Filter by duration
{ span:duration > 500ms }

# Multiple conditions
{ resource.service.name = "api" && span:status = error }

Structural Operators

# Direct parent-child relationship
{ resource.service.name = "frontend" } > { resource.service.name = "api" }

# Ancestor-descendant relationship
{ span:name = "GET /api/products" } >> { span.db.system = "postgresql" }

# Sibling relationship
{ span:name = "span-a" } ~ { span:name = "span-b" }

Aggregation Functions

# Count spans
{ } | count() > 10

# Average duration
{ } | avg(span:duration) > 20ms

# Max duration
{ span:status = error } | max(span:duration)

Metrics Functions

# Rate of errors
{ span:status = error } | rate()

# Count over time
{ span:name = "GET /:endpoint" } | count_over_time()

# Percentile latency
{ span:name = "GET /:endpoint" } | quantile_over_time(span:duration, .99)

# Group by service
{ span:status = error } | rate() by(resource.service.name)

# Top 10 by error rate
{ span:status = error } | rate() by(resource.service.name) | topk(10)

Trace Structure

Intrinsic Fields (colon separator)

FieldDescription
span:nameOperation name
span:durationElapsed time (e.g., "10ms", "1.5s")
span:statusok, error, or unset
span:kindserver, client, producer, consumer, internal
trace:durationTotal trace duration
trace:rootNameRoot span name
trace:rootServiceRoot span service

Attribute Scopes (period separator)

ScopeExampleDescription
span.span.http.methodSpan-level attributes
resource.resource.service.nameResource attributes
event.event.exception.messageEvent attributes
link.link.traceIDLink attributes

Receiver Endpoints

ProtocolPortEndpoint
OTLP gRPC4317/v1/traces
OTLP HTTP4318/v1/traces
Jaeger gRPC14250-
Jaeger Thrift HTTP14268/api/traces
Jaeger Thrift Compact6831UDP
Jaeger Thrift Binary6832UDP
Zipkin9411/api/v2/spans

Multi-Tenancy

# Enable multi-tenancy
multitenancy_enabled: true

# All requests must include X-Scope-OrgID header
# Example:
# curl -H "X-Scope-OrgID: tenant-1" http://tempo:3200/api/traces/<traceID>

Azure Identity Configuration

Workload Identity Federation (Recommended)

1. Enable Workload Identity on AKS:

az aks update \
  --name <aks-cluster> \
  --resource-group <rg> \
  --enable-oidc-issuer \
  --enable-workload-identity

2. Create User-Assigned Managed Identity:

az identity create \
  --name tempo-identity \
  --resource-group <rg>

IDENTITY_CLIENT_ID=$(az identity show --name tempo-identity --resource-group <rg> --query clientId -o tsv)

3. Assign Storage Permission:

az role assignment create \
  --role "Storage Blob Data Contributor" \
  --assignee-object-id <principal-id> \
  --scope /subscriptions/<sub>/resourceGroups/<rg>/providers/Microsoft.Storage/storageAccounts/<storage>

4. Create Federated Credential:

az identity federated-credential create \
  --name tempo-federated \
  --identity-name tempo-identity \
  --resource-group <rg> \
  --issuer <aks-oidc-issuer-url> \
  --subject system:serviceaccount:monitoring:tempo \
  --audiences api://AzureADTokenExchange

5. Configure Helm Values:

serviceAccount:
  annotations:
    azure.workload.identity/client-id: <IDENTITY_CLIENT_ID>

podLabels:
  azure.workload.identity/use: "true"

storage:
  trace:
    azure:
      use_federated_token: true

Troubleshooting

Common Issues

1. Container Not Found (Azure)

az storage container create --name tempo-traces --account-name <storage>

2. Authorization Failure (Azure)

# Verify RBAC assignment
az role assignment list --scope <storage-scope>

# Assign if missing
az role assignment create \
  --role "Storage Blob Data Contributor" \
  --assignee-object-id <principal-id> \
  --scope <storage-scope>

3. Ingester OOM

ingester:
  resources:
    limits:
      memory: 16Gi  # Increase from 8Gi

4. Query Timeout

querier:
  query_timeout: 5m
  max_concurrent_queries: 20

Diagnostic Commands

# Check pod status
kubectl get pods -n monitoring -l app.kubernetes.io/name=tempo

# Check distributor logs
kubectl logs -n monitoring -l app.kubernetes.io/component=distributor --tail=100

# Check ingester logs
kubectl logs -n monitoring -l app.kubernetes.io/component=ingester --tail=100

# Verify readiness
kubectl exec -it <tempo-pod> -n monitoring -- wget -qO- http://localhost:3200/ready

# Check ring status
kubectl port-forward svc/tempo-distributor 3200:3200 -n monitoring
curl http://localhost:3200/distributor/ring

API Reference

Trace Retrieval

# Get trace by ID
GET /api/traces/<traceID>

# Search traces (TraceQL)
GET /api/search?q={resource.service.name="api"}

# Search tags
GET /api/search/tags
GET /api/search/tag/<tag>/values

Health

GET /ready
GET /metrics

Reference Documentation

For detailed configuration by topic:

External Resources

平台分布

Claude Code

29.47%
按下载量换算103

Gemini CLI

21.59%
按下载量换算75

Cursor

16.01%
按下载量换算56

OpenCode

11.99%
按下载量换算42

Codex

7.5%
按下载量换算26

Antigravity

3.25%
按下载量换算11

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。

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