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Skills datadog-automation
📦
datadog-automation
Content revision r2 Medium Risk ⚙️ External commands🌐 Network access
Automate Datadog Monitoring Operations
Manual Datadog investigations and configuration changes consume operational time. This skill guides metrics, logs, monitors, dashboards, events, downtimes, hosts, and traces through Rube MCP.
Supports: Claude Codex Code(CC)
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Agent request
Review the Skillstore skill "datadog-automation" from https://skillstore.io/skills/sickn33-datadog-automation.md and its manifest at https://skillstore.io/api/skills/sickn33-datadog-automation/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "datadog-automation". Query average CPU usage for host web01 during the last hour.
Expected outcome:
- Average CPU usage was 64 percent, with a peak of 92 percent at 14:18 UTC.
- Usage exceeded 85 percent for seven minutes.
- No metric gaps appeared in the requested window.
Using "datadog-automation". Investigate checkout service errors from 09:00 to 09:30 UTC.
Expected outcome:
Error volume increased after 09:12 UTC and aligned with database timeout logs. Two traces show elevated database latency; deployment correlation remains unverified.
Using "datadog-automation". Schedule downtime for env:staging during tomorrow's maintenance.
Expected outcome:
Prepared a bounded staging downtime with the requested window and affected monitor scope. Creation is paused pending explicit confirmation.
Security Audit
Medium Riskv5 • 7/23/2026 Open versioned report
All 80 shell-backtick findings and eight reconnaissance findings are false positives caused by Markdown formatting, Datadog identifiers, and query examples. The Rube MCP URL is a confirmed low-severity external dependency. Semantic review found missing confirmation controls for alert suppression and irreversible dashboard deletion.
1
Files scanned
245
Lines analyzed
1
Review items
0
False positives ignored
Confirmed security concerns (2)
Medium
Alert suppression lacks confirmation controls
The workflow can mute monitors or create broad downtimes without requiring explicit confirmation, scope review, or a bounded duration.
The cited workflows expose monitor muting and scoped downtime creation. The text recommends an end time but does not require approval before suppressing alerts.
Medium
Irreversible dashboard deletion lacks confirmation
The workflow exposes permanent dashboard deletion and warns that no undo exists, but it does not require identity verification, backup, or user confirmation.
The cited section explicitly describes DATADOG_DELETE_DASHBOARD as irreversible and permanent. No mandatory confirmation or recovery step is provided.
Capability review items (1)
These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.
Low
Hardcoded URL
**Get Rube MCP**: Add `https://rube.app/mcp` as an MCP server in your client configuration. No API k
The skill explicitly directs users to add https://rube.app/mcp and authenticate Datadog through it, creating a real third-party network dependency. This matches the declared integration.
Risk Factors
⚙️ External commands (50)
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🌐 Network access (1)
Audited by: codex View Audit History →
Share & cite this report
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<iframe src="https://skillstore.io/embed/skills/sickn33-datadog-automation.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Academic citations (APA · BibTeX · CFF)
APA citation
sickn33. (2026). datadog-automation security audit report (audit version 5) [Author version unspecified]. Skillstore. https://skillstore.io/skills/sickn33-datadog-automation/audits/5BibTeX citation
@techreport{sickn33-sickn33-datadog-automation-2026,
author = {sickn33},
title = {datadog-automation security audit report (audit version 5)},
institution = {Skillstore},
year = {2026},
number = {5},
url = {https://skillstore.io/skills/sickn33-datadog-automation/audits/5},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "datadog-automation security audit report (audit version 5)"
version: "unspecified"
type: report
authors:
- name: "sickn33"
date-released: "2026-07-23"
url: "https://skillstore.io/skills/sickn33-datadog-automation/audits/5"
identifiers:
- type: other
value: "skillstore:sickn33-datadog-automation:audit:5"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: High 55
Architecture
85
Maintainability
87
Content
68
Community
83
Spec Compliance
What You Can Build
Investigate Production Incidents
Correlate service metrics, error logs, hosts, and traces within a defined incident window.
Maintain Alerting
Inspect monitor settings, prepare threshold changes, and schedule bounded maintenance downtimes.
Administer Observability Assets
Review dashboards, publish deployment events, and inventory reporting hosts across environments.
Try These Prompts
Query Host CPU
Search current Datadog tools, then query average CPU usage for {host} from {start_time} to {end_time}. Summarize peaks, averages, and data gaps.Investigate Service Errors
Investigate {service} errors between {start_time} and {end_time}. Search current tools, query relevant metrics and logs, then summarize likely causes with evidence.Prepare Maintenance Downtime
Draft a Datadog downtime for {scope} from {start_time} to {end_time}. Show affected monitors and request explicit confirmation before creating it.Correlate an Incident
Analyze incident {incident_id} across {services}. Correlate metrics, logs, monitor states, hosts, and trace {trace_id}; rank hypotheses and identify missing evidence.Best Practices
- Search current Rube tool schemas before selecting tools or parameters.
- Use narrow time windows, explicit tag scopes, bounded result limits, and pagination.
- Require explicit confirmation before mutations, especially monitor muting, downtimes, dashboard changes, and deletions.
Avoid
- Do not assume documented tool names or parameter schemas remain current.
- Do not create broad or indefinite downtimes, mute monitors, or delete dashboards without approval.
- Do not expose sensitive log, trace, host, or monitor data beyond the requested scope.
Frequently Asked Questions
What connection does this skill require?
It requires Rube MCP and an active Datadog connection authenticated through the returned authorization flow.
Does it require a Datadog API key in the prompt?
No. Authentication occurs through the Rube MCP connection flow, and credentials should never appear in prompts.
Can it change Datadog configuration?
Yes. It can create or update monitors, update dashboards, mute alerts, create downtimes, and delete dashboards when tools permit.
Can it search historical logs and metrics?
Yes, within Datadog retention limits, account permissions, valid time ranges, and endpoint rate limits.
How does it handle changing tool schemas?
Each workflow should search Rube MCP for current Datadog tool definitions before making calls.
What requires extra review?
Monitor muting, downtimes, dashboard updates, and deletions require scope review, explicit approval, and a recovery plan.
Developer Details
Author
sickn33License
MIT
Skillstore revision
r2
Version notice
The author did not declare a version.
Repository
https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/datadog-automationRef
f9e2c34b4f19c7f3e6b0a1e93227b5f77cc12526
Maintenance freshness
7/26/2026
Usage
9 downloads · 97 views
File structure
📄 SKILL.md
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