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tempotempo 搜索

Agent Skill

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。

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CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

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

简介

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。

SKILL.md

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

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02

需要根据任务场景推荐可安装能力包时

03

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需要参考平台分布和安装热度时

能力概览

能力 1

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能力 2

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能力 3

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能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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

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通过

Socket

通过

Snyk

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权限和风险

external-service

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。

来源信息

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