Read the setup guide before making changes:
Works with
Read the setup guide before making changes:
elastic-opentelemetry via pip (add to requirements.txt or equivalent)edot-bootstrap --action=install during image build to install auto-instrumentation packages for detected
librariesopentelemetry-instrument — e.g. opentelemetry-instrument gunicorn app:app or
opentelemetry-instrument python app.py. Without this, no telemetry is collectedOTEL_SERVICE_NAMEOTEL_EXPORTER_OTLP_ENDPOINT — must be the managed OTLP endpoint or EDOT Collector URL. Never use an APM
Server URL (no apm-server, no :8200, no /intake/v2/events)OTEL_EXPORTER_OTLP_HEADERS — "Authorization=ApiKey <key>" or "Authorization=Bearer <token>"OTEL_TRACES_EXPORTER, OTEL_METRICS_EXPORTER, or OTEL_LOGS_EXPORTER — the defaults are already
correctTracerProvider, no configure_azure_monitor, etc.) —
opentelemetry-instrument handles everythingelastic-apm and EDOT on the same applicationSee the EDOT Python setup guide for complete examples.
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionobservability-edot-python-instrumentExecute the skills CLI command in your project's root directory to begin installation:
Fetches observability-edot-python-instrument from elastic/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 observability-edot-python-instrument. Access via /observability-edot-python-instrument 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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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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I recommend observability-edot-python-instrument for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
observability-edot-python-instrument has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: observability-edot-python-instrument is focused, and the summary matches what you get after install.
Useful defaults in observability-edot-python-instrument — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend observability-edot-python-instrument for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
observability-edot-python-instrument has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: observability-edot-python-instrument is focused, and the summary matches what you get after install.
Useful defaults in observability-edot-python-instrument — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend observability-edot-python-instrument for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in observability-edot-python-instrument — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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