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Agent Skill · 研究检索

fleet-management(车队管理)

fleet-management 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

fleet-management 是研究检索类 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,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 42,084。

总安装 1,105周安装 47GitHub Stars 26下载 387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:fleet-management(车队管理)
来源仓库:https://github.com/grafana/skills
仓库路径:skills/fleet-management
安装命令:
npx skills add https://github.com/grafana/skills --skill fleet-management
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 fleet-management

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于集中管控多个 Grafana 实例上的技能安装与更新状态。适合大型企业环境中统一技能生命周期管理。fleet-management 属于研究检索类 Skill,可作为该场景下的辅助能力补充。支持灰度发布与回滚机制,降低大规模更新的风险。需在各实例上预先开放技能仓库的访问权限。

注意:技能更新可能引起界面变动,建议在非高峰时段操作。

来源仓库内路径:skills/fleet-management

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 fleet-management;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

fleet-management 怎么安装?

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

fleet-management 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。

fleet-management 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。

fleet-management 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。

fleet-management 用的人多吗?

公开数据是累计安装 1,105 次,近一周安装 47 次,下载 387 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。

fleet-management 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

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。
  • 需要处理研究检索类任务、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。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
fleet-management

车队管理 · 本页

1,10526接触敏感数据未明确未通过

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 Fleet Management and Alloy Configuration

Fleet Management lets you author pipeline configurations once and distribute them to many Alloy collectors remotely via OpAMP. Collectors poll for updates and apply new configurations without a restart.

Key concepts:

  • Collector - an Alloy agent instance, identified by a unique ID and set of attributes
  • Pipeline - a named Alloy configuration (YAML) stored in Fleet Management
  • Matcher - a label selector that maps a pipeline to matching collectors
  • Attributes - key/value labels on a collector used for targeting (e.g. env=production)

Step 1: Check the current state

BASE=https://fleet-management-prod-us-east-0.grafana.net
TOKEN=<STACK_ID>:<API_TOKEN>

# List all registered collectors and their health status
curl -s -X POST "$BASE/collector.v1.CollectorService/ListCollectors" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{}' | jq '.collectors[] | {id, name, remoteConfigStatus}'

# List all pipelines
curl -s -X POST "$BASE/pipeline.v1.PipelineService/ListPipelines" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{}'

In the Grafana Cloud UI: Connections > Collector > Fleet Management > Collector Inventory.

Healthy collectors show REMOTE_CONFIG_STATUS_APPLIED. Degraded collectors show REMOTE_CONFIG_STATUS_FAILED with a remoteConfigStatusMessage describing the error.


Step 2: Understand the pipeline YAML format

Pipelines are valid Alloy configuration files. Alloy uses a HCL-like syntax called River.

// Basic metrics pipeline: scrape Prometheus metrics and forward to Grafana Cloud
prometheus.scrape "default" {
  targets    = discovery.relabel.filtered.output
  forward_to = [prometheus.remote_write.grafana_cloud.receiver]
  scrape_interval = "60s"
}

prometheus.remote_write "grafana_cloud" {
  endpoint {
    url = "https://prometheus-prod-01-eu-west-0.grafana.net/api/prom/push"
    basic_auth {
      username = "<METRICS_USERNAME>"
      password = env("GRAFANA_CLOUD_API_KEY")
    }
  }
}

Key Alloy component categories:

CategoryExample components
Discoverydiscovery.kubernetes, discovery.docker, discovery.relabel
Metricsprometheus.scrape, prometheus.remote_write, prometheus.operator.*
Logsloki.source.file, loki.source.kubernetes, loki.write
Tracesotelcol.receiver.otlp, otelcol.exporter.otlp
Profilespyroscope.scrape, pyroscope.write
Transformationotelcol.processor.batch, otelcol.processor.filter

Reference: Alloy component documentation


Step 3: Create a pipeline

# Create a pipeline via API (contents is plain text Alloy config, not base64)
curl -s -X POST "$BASE/pipeline.v1.PipelineService/CreatePipeline" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "k8s-metrics",
    "contents": "prometheus.scrape \"default\" {\n  targets = []\n  forward_to = []\n}",
    "matchers": [
      {"name": "env", "value": "production", "type": "EQUAL"}
    ]
  }'

In the UI: Fleet Management > Remote Configuration > Create pipeline. The wizard offers:

  1. Start from a template (Kubernetes, host metrics, logs, traces, profiles)
  2. Duplicate an existing pipeline
  3. Write from scratch with the inline editor

Step 4: Assign pipelines to collectors with matchers

Matchers use label selectors to map a pipeline to collectors. A collector receives all pipelines whose matchers match its attributes.

{
  "matchers": [
    "env=\"production\"",
    "team=\"platform\""
  ]
}

This assigns the pipeline to any collector with both env=production AND team=platform.

Matcher syntax:

OperatorExampleMeaning
=env="production"Exact match
!=env!="dev"Not equal
=~region=~"us-.*"Regex match
!~region!~"eu-.*"Regex not match

Apply matchers when creating or updating a pipeline:

# Matchers are set in CreatePipeline or UpdatePipeline
curl -s -X POST "$BASE/pipeline.v1.PipelineService/UpdatePipeline" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "id": "<PIPELINE_ID>",
    "matchers": [
      {"name": "env",  "value": "production", "type": "EQUAL"},
      {"name": "team", "value": "platform",   "type": "EQUAL"}
    ]
  }'

Matcher type values: EQUAL, NOT_EQUAL, REGEX, NOT_REGEX

A pipeline with no matchers is saved but deployed to zero collectors.


Step 5: Set collector attributes

Attributes are the labels that matchers target. Set them from the UI (Collector Inventory > select collector > Edit attributes) or via API:

curl -s -X POST "$BASE/collector.v1.CollectorService/UpdateCollector" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "id": "<COLLECTOR_ID>",
    "attributes": [
      {"name": "env",    "value": "production"},
      {"name": "team",   "value": "platform"},
      {"name": "region", "value": "us-east-1"}
    ]
  }'

Alloy sets some attributes automatically on registration:

  • platform - OS platform (linux, darwin, windows)
  • arch - CPU architecture (amd64, arm64)
  • alloy_version - Alloy version string

Custom attributes must be set explicitly — either via the API or by the collector's startup config.


Step 6: Install Alloy with remote configuration enabled

For Alloy to receive remote configuration from Fleet Management, it needs:

  1. An API token with Fleet Management access
  2. The remotecfg block in its local (bootstrap) configuration
// bootstrap.alloy -- the only local config file Alloy needs
remotecfg {
  url = "https://<FLEET_MANAGEMENT_HOST>"

  basic_auth {
    username = "<STACK_ID>"
    password = env("GRAFANA_CLOUD_API_KEY")
  }

  poll_frequency = "1m"

  // Attributes for this collector instance
  attributes = {
    "env"    = env("ENVIRONMENT"),
    "team"   = "platform",
    "region" = env("AWS_REGION"),
  }
}

Kubernetes deployment:

# values.yaml for grafana/alloy Helm chart
alloy:
  configMap:
    content: |
      remotecfg {
        url = "https://<FLEET_MANAGEMENT_HOST>"
        basic_auth {
          username = "<STACK_ID>"
          password = env("GRAFANA_CLOUD_API_KEY")
        }
        poll_frequency = "1m"
        attributes = {
          "env" = "production",
          "cluster" = env("CLUSTER_NAME"),
        }
      }
  extraEnv:
    - name: GRAFANA_CLOUD_API_KEY
      valueFrom:
        secretKeyRef:
          name: grafana-cloud-credentials
          key: api-key

Step 7: Troubleshoot collector health

Check remote config status:

# List collectors with FAILED status
curl -s -X POST "$BASE/collector.v1.CollectorService/ListCollectors" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{}' | jq '.collectors[] | select(.remoteConfigStatus == "REMOTE_CONFIG_STATUS_FAILED") | {id, name, remoteConfigStatusMessage}'

Common failure patterns:

Status messageRoot causeFix
syntax error at line NInvalid Alloy River syntaxFix the pipeline YAML; validate before deploying
component not found: XAlloy version too old for a componentUpgrade Alloy or use an older API
failed to unmarshal configBase64 encoding errorRe-encode the config correctly
authentication failedWrong API tokenRotate and re-apply the token
connection refusedCollector can't reach Fleet ManagementCheck network/firewall rules

Check Alloy logs directly:

# Kubernetes
kubectl logs -n monitoring -l app.kubernetes.io/name=alloy --tail=50 | grep -i "remote\|error"

# Systemd
journalctl -u alloy --since "1h ago" | grep -i "remote\|error"

Check the Alloy UI (port 12345 by default) at http://<COLLECTOR_HOST>:12345:

  • Graph tab: shows component wiring and health per component
  • Components tab: lists all components and their current config
  • Clustering tab: shows clustering state if enabled

Step 8: Use the Grafana Assistant for pipeline work

The Grafana Assistant understands Fleet Management and can:

  • Explain what a pipeline configuration does
  • Identify syntax errors and suggest fixes
  • Optimize pipelines for performance or cost
  • Generate Mermaid diagrams of component wiring

Via the UI: In the Remote Configuration page, select a pipeline and click the Assistant button. Options: Explain, Validate/Fix, Optimize, Visualize.

Via API (for automation): The Assistant exposes Fleet Management tools:

  • fleetManagementRead - list collectors and pipelines
  • fleetManagementWrite - update pipeline configurations
  • alloyConfigValidation - validate Alloy River syntax

References

平台分布

Codex

38.51%
按下载量换算149

Claude

30.03%
按下载量换算116

Cursor

18.18%
按下载量换算70

Gemini CLI

9.33%
按下载量换算36

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

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。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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