Agent skill

Datadog Automation

by davepoon in davepoon/buildwithclaude

Automate Datadog tasks via Rube MCP (Composio): query metrics, search logs, manage monitors/dashboards, create events and downtimes.

MITAuto-check passedProductivity & Automation

Install Datadog Automation

skills CLI
$ npx skills add davepoon/buildwithclaude --skill datadog-automation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install davepoon/buildwithclaude datadog-automation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/davepoon/buildwithclaude.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/all-skills/skills/datadog-automation .claude/skills/datadog-automation && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
datadog-automation
GitHub stars
3.6k
Used in
7 other repos
Token cost
~2.3k tokens
SKILL.md length
1,059 words
Files
1
Skills in repo
246
Repo updated
First seen
Licence
MIT

At a glance

Automate Datadog tasks via Rube MCP (Composio): query metrics, search logs, manage monitors/dashboards, create events and downtimes.

  • Works in 6 steps: Query and Explore Metrics → Search and Analyze Logs → Manage Monitors → …
  • Tasks that involve App automation through connectors
  • SKILL.md covers Prerequisites, Setup, Core Workflows and Common Patterns, plus 2 more sections
  • Reaches rube.app

What it does

Datadog Automation is an agent skill from davepoon/buildwithclaude. Automate Datadog tasks via Rube MCP (Composio): query metrics, search logs, manage monitors/dashboards, create events and downtimes. Always search tools first for current schemas.

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Productivity & Automation, covering App automation through connectors. It works with Datadog and Composio. The repository describes itself as: A single hub to find Claude Skills, Agents, Commands, Hooks, Plugins, and Marketplace collections to extend Claude Code, Claude Desktop, Agent SDK and OpenClaw. The licence is MIT.

When your agent uses it

  • Tasks that involve App automation through connectors

Example prompts

  • “/datadog-automation”

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Query and Explore Metrics
  2. Search and Analyze Logs
  3. Manage Monitors
  4. Manage Dashboards
  5. Create Events and Manage Downtimes
  6. Manage Hosts and Traces

What it can do on your machine

Read from SKILL.md and the folder at commit 616deb5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • rube.app

    Also links to:

    • composio.dev

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Datadog Automation loads about 2.3k tokens when it runs. Until then it costs about 50 tokens; SKILL.md has 1,059 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~50
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from davepoon/buildwithclaude at commit 616deb5, republished under its MIT licence (© davepoon). 1,059 words, ~2,347 tokens.

Download SKILL.mdSave it as .claude/skills/datadog-automation/SKILL.md (or your agent's skills folder).
name
datadog-automation
description
Automate Datadog tasks via Rube MCP (Composio): query metrics, search logs, manage monitors/dashboards, create events and downtimes. Always search tools first for current schemas.
requires.mcp
rube
category
observability

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
Show full SKILL.md (460 more words)Show less
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

Powered by Composio

© davepoon, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in plugins/all-skills/skills/datadog-automation of davepoon/buildwithclaude.

Open the folder on GitHubat commit 616deb5

Used in 7 other repositories

We found 17 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 7 other GitHub owners. This page covers the copy in davepoon/buildwithclaude, which our catalogue first saw on October 7, 2026.

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Works with

Questions about Datadog Automation

What does Datadog Automation do?

Automate Datadog tasks via Rube MCP (Composio): query metrics, search logs, manage monitors/dashboards, create events and downtimes. Datadog Automation is an agent skill from davepoon/buildwithclaude. Automate Datadog tasks via Rube MCP (Composio): query metrics, search logs, manage monitors/dashboards, create events and downtimes.

When should I use Datadog Automation?

Datadog Automation fits situations like: tasks that involve App automation through connectors.

How do I install Datadog Automation in Claude Code?

Run `npx skills add davepoon/buildwithclaude --skill datadog-automation -a claude-code`. Or copy the skill folder (plugins/all-skills/skills/datadog-automation in davepoon/buildwithclaude) into .claude/skills/datadog-automation in your project. Claude Code loads it when a task matches its description.

How do I install Datadog Automation in Codex?

Run `npx skills add davepoon/buildwithclaude --skill datadog-automation -a codex`. Or copy the skill folder (plugins/all-skills/skills/datadog-automation in davepoon/buildwithclaude) into .agents/skills/datadog-automation in your project. Codex loads it when a task matches its description.

Can I use Datadog Automation in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add davepoon/buildwithclaude --skill datadog-automation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/datadog-automation, .gemini/skills/datadog-automation, .github/skills/datadog-automation and .opencode/skills/datadog-automation in your project.

What does Datadog Automation need to run?

SKILL.md names no scripts, command-line tools or credentials: Datadog Automation is instructions for the agent only.

Does Datadog Automation access the network?

SKILL.md names 2 domains. In commands or code: rube.app; the agent is likely to contact it when it follows the instructions. As links in the text: composio.dev. This is read from the text; nothing was executed.

Is Datadog Automation safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Datadog Automation use?

Datadog Automation is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Datadog Automation use?

About 2.3k tokens (SKILL.md is roughly 9.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Datadog Automation?

Skills that share tags, products or a category with Datadog Automation: Composio (yc-software/qm, 15k stars), Connect Apps with Composio (ComposioHQ/awesome-claude-skills, 77k stars), Abuselpdb Automation (ComposioHQ/awesome-claude-skills, 77k stars) and Accredible Certificates Automation (ComposioHQ/awesome-claude-skills, 77k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Datadog Automation?

davepoon (a GitHub user) maintains it in davepoon/buildwithclaude, which has 3,605 GitHub stars. The repository holds 246 skills in this directory. The repository was last updated on October 9, 2026.

Source: davepoon/buildwithclaude on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.