sentry

Use when the user asks to inspect Sentry issues or events, summarize recent production errors, or pull basic Sentry health data via the Sentry API; perform read-only queries with the bundled script and require `SENTRY_AUTH_TOKEN`.

685 stars

Best use case

sentry is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Use when the user asks to inspect Sentry issues or events, summarize recent production errors, or pull basic Sentry health data via the Sentry API; perform read-only queries with the bundled script and require `SENTRY_AUTH_TOKEN`.

Teams using sentry should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/sentry/SKILL.md --create-dirs "https://raw.githubusercontent.com/openai/plugins/main/plugins/sentry/skills/sentry/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/sentry/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How sentry Compares

Feature / AgentsentryStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Use when the user asks to inspect Sentry issues or events, summarize recent production errors, or pull basic Sentry health data via the Sentry API; perform read-only queries with the bundled script and require `SENTRY_AUTH_TOKEN`.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Sentry (Read-only Observability)

## Quick start

- If not already authenticated, ask the user to provide a valid `SENTRY_AUTH_TOKEN` (read-only scopes such as `project:read`, `event:read`) or to log in and create one before running commands.
- Set `SENTRY_AUTH_TOKEN` as an env var.
- Optional defaults: `SENTRY_ORG`, `SENTRY_PROJECT`, `SENTRY_BASE_URL`.
- Defaults: org/project `{your-org}`/`{your-project}`, time range `24h`, environment `prod`, limit 20 (max 50).
- Always call the Sentry API (no heuristics, no caching).

If the token is missing, give the user these steps:
1. Create a Sentry auth token: https://sentry.io/settings/account/api/auth-tokens/
2. Create a token with read-only scopes such as `project:read`, `event:read`, and `org:read`.
3. Set `SENTRY_AUTH_TOKEN` as an environment variable in their system.
4. Offer to guide them through setting the environment variable for their OS/shell if needed.
- Never ask the user to paste the full token in chat. Ask them to set it locally and confirm when ready.

## Core tasks (use bundled script)

Use `scripts/sentry_api.py` for deterministic API calls. It handles pagination and retries once on transient errors.

## Bundled script path

```bash
export SENTRY_API="plugins/sentry/skills/sentry/scripts/sentry_api.py"
```

If you are running from an installed plugin copy instead of this repo checkout, use the same
`skills/sentry/scripts/sentry_api.py` path inside the installed plugin directory.

### 1) List issues (ordered by most recent)

```bash
python3 "$SENTRY_API" \
  --org {your-org} \
  --project {your-project} \
  list-issues \
  --environment prod \
  --time-range 24h \
  --limit 20 \
  --query "is:unresolved"
```

### 2) Resolve an issue short ID to issue ID

```bash
python3 "$SENTRY_API" \
  --org {your-org} \
  --project {your-project} \
  list-issues \
  --query "ABC-123" \
  --limit 1
```

Use the returned `id` for issue detail or events.

### 3) Issue detail

```bash
python3 "$SENTRY_API" \
  --org {your-org} \
  issue-detail \
  1234567890
```

### 4) Issue events

```bash
python3 "$SENTRY_API" \
  --org {your-org} \
  issue-events \
  1234567890 \
  --environment prod \
  --time-range 24h \
  --limit 20
```

### 5) Event detail (no stack traces by default)

```bash
python3 "$SENTRY_API" \
  --org {your-org} \
  --project {your-project} \
  event-detail \
  abcdef1234567890
```

## API requirements

Always use these endpoints (GET only):

- List issues: `/api/0/projects/{org_slug}/{project_slug}/issues/`
- Issue detail: `/api/0/organizations/{org_slug}/issues/{issue_id}/`
- Events for issue: `/api/0/organizations/{org_slug}/issues/{issue_id}/events/`
- Event detail: `/api/0/projects/{org_slug}/{project_slug}/events/{event_id}/`

## Inputs and defaults

- `org_slug`: default to `{your-org}` (required for issue detail, issue events, and event detail).
- `project_slug`: default to `{your-project}` (required for list issues and event detail).
- `time_range`: default `24h` (pass as `statsPeriod` for list issues and issue events).
- `environment`: default `prod` (used by list issues and issue events).
- `limit`: default 20, max 50 (paginate until limit reached).
- `search_query`: optional `query` parameter.
- `issue_short_id`: resolve via list-issues query first.

## 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.

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