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datadog-automation数据狗自动化

Agent Skill

用于辅助数据整理、表格处理、CSV/Excel 分析、指标计算和图表准备。它适合让 Agent 清洗字段、汇总数据、发现异常、生成统计口径或把分析结果转成可读说明。使用时需要确认数据来源、字段含义和时间范围,避免把样本数据当全量事实;涉及敏感数据、导出文件或批量写回时,应先确认权限和脱敏边界。

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771

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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

2

许可证

unknown

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:datadog-automation(数据狗自动化)
来源仓库:https://github.com/davepoon/buildwithclaude
仓库路径:skills/datadog-automation
安装命令:
npx skills add https://github.com/davepoon/buildwithclaude --skill datadog-automation
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/davepoon/buildwithclaude --skill datadog-automation

简介

datadog-automation 用于自动化 Datadog 监控和观测操作,包括指标查询和告警管理。

  • 适用于系统监控、性能分析和运维告警处理等场景。
  • 支持仪表板查看、日志检索和事件跟踪等功能。
  • 需先配置 Rube MCP 并连接 Datadog 账户,通过 npx 安装,注意数据隐私和访问权限控制。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Datadog Automation via Rube MCP

Automate Datadog monitoring and observability operations through Composio's Datadog toolkit via Rube MCP.

Toolkit docs: composio.dev/toolkits/datadog

Prerequisites

  • Rube MCP must be connected (RUBE_SEARCH_TOOLS available)
  • Active Datadog connection via RUBE_MANAGE_CONNECTIONS with toolkit datadog
  • Always call RUBE_SEARCH_TOOLS first to get current tool schemas

Setup

Get Rube MCP: Add https://rube.app/mcp as an MCP server in your client configuration. No API keys needed — just add the endpoint and it works.

  1. Verify Rube MCP is available by confirming RUBE_SEARCH_TOOLS responds
  2. Call RUBE_MANAGE_CONNECTIONS with toolkit datadog
  3. If connection is not ACTIVE, follow the returned auth link to complete Datadog authentication
  4. Confirm connection status shows ACTIVE before running any workflows

Core Workflows

1. Query and Explore Metrics

When to use: User wants to query metric data or list available metrics

Tool sequence:

  1. DATADOG_LIST_METRICS - List available metric names [Optional]
  2. DATADOG_QUERY_METRICS - Query metric time series data [Required]

Key parameters:

  • query: Datadog metric query string (e.g., avg:system.cpu.user{host:web01})
  • from: Start timestamp (Unix epoch seconds)
  • to: End timestamp (Unix epoch seconds)
  • q: Search string for listing metrics

Pitfalls:

  • Query syntax follows Datadog's metric query format: aggregation:metric_name{tag_filters}
  • from and to are Unix epoch timestamps in seconds, not milliseconds
  • Valid aggregations: avg, sum, min, max, count
  • Tag filters use curly braces: {host:web01,env:prod}
  • Time range should not exceed Datadog's retention limits for the metric type

2. Search and Analyze Logs

When to use: User wants to search log entries or list log indexes

Tool sequence:

  1. DATADOG_LIST_LOG_INDEXES - List available log indexes [Optional]
  2. DATADOG_SEARCH_LOGS - Search logs with query and filters [Required]

Key parameters:

  • query: Log search query using Datadog log query syntax
  • from: Start time (ISO 8601 or Unix timestamp)
  • to: End time (ISO 8601 or Unix timestamp)
  • sort: Sort order ('asc' or 'desc')
  • limit: Number of log entries to return

Pitfalls:

  • Log queries use Datadog's log search syntax: service:web status:error
  • Search is limited to retained logs within the configured retention period
  • Large result sets require pagination; check for cursor/page tokens
  • Log indexes control routing and retention; filter by index if known

3. Manage Monitors

When to use: User wants to create, update, mute, or inspect monitors

Tool sequence:

  1. DATADOG_LIST_MONITORS - List all monitors with filters [Required]
  2. DATADOG_GET_MONITOR - Get specific monitor details [Optional]
  3. DATADOG_CREATE_MONITOR - Create a new monitor [Optional]
  4. DATADOG_UPDATE_MONITOR - Update monitor configuration [Optional]
  5. DATADOG_MUTE_MONITOR - Silence a monitor temporarily [Optional]
  6. DATADOG_UNMUTE_MONITOR - Re-enable a muted monitor [Optional]

Key parameters:

  • monitor_id: Numeric monitor ID
  • name: Monitor display name
  • type: Monitor type ('metric alert', 'service check', 'log alert', 'query alert', etc.)
  • query: Monitor query defining the alert condition
  • message: Notification message with @mentions
  • tags: Array of tag strings
  • thresholds: Alert threshold values (critical, warning, ok)

Pitfalls:

  • Monitor type must match the query type; mismatches cause creation failures
  • message supports @mentions for notifications (e.g., @slack-channel, @pagerduty)
  • Thresholds vary by monitor type; metric monitors need critical at minimum
  • Muting a monitor suppresses notifications but the monitor still evaluates
  • Monitor IDs are numeric integers

4. Manage Dashboards

When to use: User wants to list, view, update, or delete dashboards

Tool sequence:

  1. DATADOG_LIST_DASHBOARDS - List all dashboards [Required]
  2. DATADOG_GET_DASHBOARD - Get full dashboard definition [Optional]
  3. DATADOG_UPDATE_DASHBOARD - Update dashboard layout or widgets [Optional]
  4. DATADOG_DELETE_DASHBOARD - Remove a dashboard (irreversible) [Optional]

Key parameters:

  • dashboard_id: Dashboard identifier string
  • title: Dashboard title
  • layout_type: 'ordered' (grid) or 'free' (freeform positioning)
  • widgets: Array of widget definition objects
  • description: Dashboard description

Pitfalls:

  • Dashboard IDs are alphanumeric strings (e.g., 'abc-def-ghi'), not numeric
  • layout_type cannot be changed after creation; must recreate the dashboard
  • Widget definitions are complex nested objects; get existing dashboard first to understand structure
  • DELETE is permanent; there is no undo

5. Create Events and Manage Downtimes

When to use: User wants to post events or schedule maintenance downtimes

Tool sequence:

  1. DATADOG_LIST_EVENTS - List existing events [Optional]
  2. DATADOG_CREATE_EVENT - Post a new event [Required]
  3. DATADOG_CREATE_DOWNTIME - Schedule a maintenance downtime [Optional]

Key parameters for events:

  • title: Event title
  • text: Event body text (supports markdown)
  • alert_type: Event severity ('error', 'warning', 'info', 'success')
  • tags: Array of tag strings

Key parameters for downtimes:

  • scope: Tag scope for the downtime (e.g., host:web01)
  • start: Start time (Unix epoch)
  • end: End time (Unix epoch; omit for indefinite)
  • message: Downtime description
  • monitor_id: Specific monitor to downtime (optional, omit for scope-based)

Pitfalls:

  • Event text supports Datadog's markdown format including @mentions
  • Downtimes scope uses tag syntax: host:web01, env:staging
  • Omitting end creates an indefinite downtime; always set an end time for maintenance
  • Downtime monitor_id narrows to a single monitor; scope applies to all matching monitors

6. Manage Hosts and Traces

When to use: User wants to list infrastructure hosts or inspect distributed traces

Tool sequence:

  1. DATADOG_LIST_HOSTS - List all reporting hosts [Required]
  2. DATADOG_GET_TRACE_BY_ID - Get a specific distributed trace [Optional]

Key parameters:

  • filter: Host search filter string
  • sort_field: Sort hosts by field (e.g., 'name', 'apps', 'cpu')
  • sort_dir: Sort direction ('asc' or 'desc')
  • trace_id: Distributed trace ID for trace lookup

Pitfalls:

  • Host list includes all hosts reporting to Datadog within the retention window
  • Trace IDs are long numeric strings; ensure exact match
  • Hosts that stop reporting are retained for a configured period before removal

Common Patterns

Monitor Query Syntax

Metric alerts:

avg(last_5m):avg:system.cpu.user{env:prod} > 90

Log alerts:

logs("service:web status:error").index("main").rollup("count").last("5m") > 10

Tag Filtering

  • Tags use key:value format: host:web01, env:prod, service:api
  • Multiple tags: {host:web01,env:prod} (AND logic)
  • Wildcard: host:web*

Pagination

  • Use page and page_size or offset-based pagination depending on endpoint
  • Check response for total count to determine if more pages exist
  • Continue until all results are retrieved

Known Pitfalls

Timestamps:

  • Most endpoints use Unix epoch seconds (not milliseconds)
  • Some endpoints accept ISO 8601; check tool schema
  • Time ranges should be reasonable (not years of data)

Query Syntax:

  • Metric queries: aggregation:metric{tags}
  • Log queries: field:value pairs
  • Monitor queries vary by type; check Datadog documentation

Rate Limits:

  • Datadog API has per-endpoint rate limits
  • Implement backoff on 429 responses
  • Batch operations where possible

Quick Reference

TaskTool SlugKey Params
Query metricsDATADOG_QUERY_METRICSquery, from, to
List metricsDATADOG_LIST_METRICSq
Search logsDATADOG_SEARCH_LOGSquery, from, to, limit
List log indexesDATADOG_LIST_LOG_INDEXES(none)
List monitorsDATADOG_LIST_MONITORStags
Get monitorDATADOG_GET_MONITORmonitor_id
Create monitorDATADOG_CREATE_MONITORname, type, query, message
Update monitorDATADOG_UPDATE_MONITORmonitor_id
Mute monitorDATADOG_MUTE_MONITORmonitor_id
Unmute monitorDATADOG_UNMUTE_MONITORmonitor_id
List dashboardsDATADOG_LIST_DASHBOARDS(none)
Get dashboardDATADOG_GET_DASHBOARDdashboard_id
Update dashboardDATADOG_UPDATE_DASHBOARDdashboard_id, title, widgets
Delete dashboardDATADOG_DELETE_DASHBOARDdashboard_id
List eventsDATADOG_LIST_EVENTSstart, end
Create eventDATADOG_CREATE_EVENTtitle, text, alert_type
Create downtimeDATADOG_CREATE_DOWNTIMEscope, start, end
List hostsDATADOG_LIST_HOSTSfilter, sort_field
Get traceDATADOG_GET_TRACE_BY_IDtrace_id

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平台分布

Codex

35.59%
按下载量换算31

Claude

30.56%
按下载量换算27

Cursor

20.98%
按下载量换算18

Gemini CLI

9.79%
按下载量换算9

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