Automatically detect and configure Sentry monitoring for LLM calls, agents, and AI SDKs.
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
Time estimate: 15-45 minutes depending on use case complexity
Prerequisites
Submit your Claude Code skill and start earning
epx add getsentry/sentry-agent-skills --skill sentry-setup-ai-monitoringCompatible with
Supported agents
Auto-detects installed AI packages (OpenAI, Anthropic, LangChain, Google GenAI, Vercel AI, Pydantic AI, and others) and enables appropriate integrations with zero manual registration in Python
Requires tracing enabled ( tracesSampleRate > 0 ) and supports manual span instrumentation via gen_ai.* operation types for unsupported SDKs
Captures model, token counts, and latency by default; prompt and
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionsentry-setup-ai-monitoringExecute the skills CLI command in your project's root directory to begin installation:
epx add getsentry/sentry-agent-skills --skill sentry-setup-ai-monitoringFetches sentry-setup-ai-monitoring from getsentry/sentry-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:
.cursor/skills/sentry-setup-ai-monitoring
Restart Cursor to activate sentry-setup-ai-monitoring. Access via /sentry-setup-ai-monitoringin your agent's command palette.
Learn more:View source on GitHubSkills CLI docsAbout CursorWhat are agent skills?
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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sentry-setup-ai-monitoring is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Solid pick for teams standardizing on skills: sentry-setup-ai-monitoring is focused, and the summary matches what you get after install.
sentry-setup-ai-monitoring reduced setup friction for our internal harness; good balance of opinion and flexibility.
Useful defaults in sentry-setup-ai-monitoring — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: sentry-setup-ai-monitoring is focused, and the summary matches what you get after install.
sentry-setup-ai-monitoring is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in sentry-setup-ai-monitoring — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
We added sentry-setup-ai-monitoring from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
sentry-setup-ai-monitoring fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Keeps context tight: sentry-setup-ai-monitoring is the kind of skill you can hand to a new teammate without a long onboarding doc.
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