Generated banner for Sentry
Generated logo for Sentry

Sentry

OpenAIOfficialPublished by OpenAI

  • Skill
  • Tool integration
  • Cloud and DevOps
  • Apache-2.0
  • Medium risk

From the author

Use when the user asks to inspect Sentry issues or events, summarize recent production errors, or pull basic Sentry health data via the Sentry CLI; perform read-only queries using the `sentry` command.
— the description by OpenAI

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The Sentry skill enables AI agents to interact with Sentry via the command line interface. It provides a structured approach to querying unresolved issues, retrieving event details, and performing root cause analysis or fix planning. The skill emphasizes secure, read-only access, leveraging auto-detection for organizational and project contexts while supporting explicit overrides when necessary.

What it does

  • Lists unresolved production issues with customizable filters and time ranges.
  • Retrieves detailed information for specific Sentry issues using short IDs.
  • Fetches event-specific data for deep-dive troubleshooting.
  • Provides AI-powered root cause analysis and fix planning for identified issues.
  • Allows arbitrary API access for advanced queries via schema discovery.
  • Ensures secure data handling by redacting PII and preventing token exposure.

When to use it

  • When you need to summarize recent production errors or monitor system health.
  • When investigating specific application crashes or performance bottlenecks.
  • When you need to audit unresolved issues to prioritize development tasks.
  • When you require programmatic access to Sentry data for reporting or analysis.

Advantages

  • Automates the retrieval of observability data directly within the agent workflow.
  • Reduces manual context switching between the terminal and the Sentry dashboard.
  • Supports machine-readable JSON output for seamless data integration.
  • Provides built-in AI assistance for interpreting complex error logs and planning fixes.

Usage examples

“List the top 10 open issues for prod in the last 24h.”
The agent executes a filtered Sentry CLI command and returns a list of unresolved issues including titles, short IDs, and occurrence counts.
“Explain the root cause of issue ABC-123.”
The agent uses the Sentry CLI to perform an AI-powered analysis of the specified issue and provides a summary of the underlying problem.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/openai/sentry/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip sentry.zip -d .agents/skills

Documentation by OpenAI

Sentry (Read-only Observability)

Quick start

  • If not already authenticated, ask the user to run sentry auth login or set SENTRY_AUTH_TOKEN as an env var.

  • The CLI auto-detects org/project from DSNs in .env files, source code, config defaults, and directory names. Only specify <org>/<project> if auto-detection fails or picks the wrong target.

  • Defaults: time range 24h, environment production, limit 20.

  • Always use --json when processing output programmatically. Use --json --fields to select specific fields and reduce output size.

  • Use sentry schema <resource> to discover API endpoints quickly.

If the CLI is not installed, give the user these steps:

  1. Install the Sentry CLI: curl https://cli.sentry.dev/install -fsS | bash

  2. Authenticate: sentry auth login

  3. Confirm authentication: sentry auth status

  • Never ask the user to paste the full token in chat. Ask them to set it locally and confirm when ready.

Core tasks (use Sentry CLI)

Use the sentry CLI for all queries. It handles authentication, org/project detection, pagination, and retries automatically. Use --json for machine-readable output.

1) List issues (ordered by most recent)
sentry issue list \
  --query "is:unresolved environment:production" \
  --period 24h \
  --limit 20 \
  --json --fields shortId,title,priority,level,status

If auto-detection doesn't resolve org/project, pass them explicitly:

sentry issue list {your-org}/{your-project} \
  --query "is:unresolved environment:production" \
  --period 24h \
  --limit 20 \
  --json
2) Resolve an issue short ID to issue detail
sentry issue view {ABC-123} --json

Use the short ID format (e.g., ABC-123), not the numeric ID.

3) Issue detail
sentry issue view {ABC-123}
4) Issue events
sentry issue events {ABC-123} --limit 20 --json
5) Event detail
sentry event view {your-org}/{your-project}/{event_id} --json
6) AI-powered root cause analysis
sentry issue explain {ABC-123}
7) AI-powered fix plan
sentry issue plan {ABC-123}

Fallback: arbitrary API access

For endpoints not covered by dedicated CLI commands, use sentry api:

sentry api /api/0/organizations/{your-org}/ --method GET

Use sentry schema to discover available API endpoints:

sentry schema issues

Inputs and defaults

  • org_slug, project_slug: auto-detected by the CLI from DSNs, env vars, and directory names. Override with positional {your-org}/{your-project} if auto-detection fails.

  • time_range: default 24h (pass as --period 24h).

  • environment: default prod (pass as part of --query, e.g., environment:production).

  • limit: default 20 (pass as --limit).

  • search_query: optional --query parameter, uses Sentry search syntax (e.g., is:unresolved, assigned:me).

  • issue_short_id: use directly with sentry issue view.

Output formatting rules

  • Issue list: show title, short_id, status, first_seen, last_seen, count, environments, top_tags; order by most recent.

  • Event detail: include culprit, timestamp, environment, release, url.

  • If no results, state explicitly.

  • Redact PII in output (emails, IPs). Do not print raw stack traces.

  • Never echo auth tokens.

Golden test inputs

  • Org: {your-org}

  • Project: {your-project}

  • Issue short ID: {ABC-123}

Example prompt: "List the top 10 open issues for prod in the last 24h." Expected: ordered list with titles, short IDs, counts, last seen.

Files

Requirements and compatibility

Written for: OpenAI Codex

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs network access

Security

What our scanner noticed· Medium risk

  • Instructions that use the network
  • Downloads piped into a shell

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by
OpenAI
Publisher
OpenAI (Official)
Source
openai/skills · skills/.curated/sentry · commit 49f948f
Licence
Apache License 2.0 (redistribution allowed)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by OpenAI or OpenAI.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download sentry.zip