Use this skill to locate Datadog documentation and limits.
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AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiondd-docsExecute the skills CLI command in your project's root directory to begin installation:
Fetches dd-docs from datadog-labs/agent-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate dd-docs. Access via /dd-docs in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Use this skill to locate Datadog documentation and limits.
Datadog provides an LLM-optimized documentation index at:
https://docs.datadoghq.com/llms.txt
This file contains:
.md to URLs)Fetch the index to understand available documentation:
curl -s https://docs.datadoghq.com/llms.txt | head -100
Search for specific topics:
Examples:
curl -s https://docs.datadoghq.com/llms.txt | grep -i "monitors"
curl -s https://docs.datadoghq.com/llms.txt | grep -i "apm"
curl -s https://docs.datadoghq.com/llms.txt | grep -i "logs"
curl -s https://docs.datadoghq.com/monitors.md
curl -s https://docs.datadoghq.com/tracing.md
| Topic | URL |
|---|---|
| APM/Tracing | https://docs.datadoghq.com/tracing/ |
| Logs | https://docs.datadoghq.com/logs/ |
| Metrics | https://docs.datadoghq.com/metrics/ |
| Monitors | https://docs.datadoghq.com/monitors/ |
| Dashboards | https://docs.datadoghq.com/dashboards/ |
| Security | https://docs.datadoghq.com/security/ |
| Synthetics | https://docs.datadoghq.com/synthetics/ |
| RUM | https://docs.datadoghq.com/real_user_monitoring/ |
| Incidents | https://docs.datadoghq.com/service_management/incident_management/ |
| API Reference | https://docs.datadoghq.com/api/ |
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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Registry listing for dd-docs matched our evaluation — installs cleanly and behaves as described in the markdown.
Solid pick for teams standardizing on skills: dd-docs is focused, and the summary matches what you get after install.
Keeps context tight: dd-docs is the kind of skill you can hand to a new teammate without a long onboarding doc.
dd-docs has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in dd-docs — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
dd-docs is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
I recommend dd-docs for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: dd-docs is the kind of skill you can hand to a new teammate without a long onboarding doc.
Solid pick for teams standardizing on skills: dd-docs is focused, and the summary matches what you get after install.
dd-docs fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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