sentry
Inspect Sentry issues, summarize production errors, and pull health data via the Sentry API (read-only). Use when user says "check Sentry", "what errors in production?", "summarize Sentry issues", "recent crashes", or "production error report". Requires SENTRY_AUTH_TOKEN. Do NOT use for setting up Sentry SDK, configuring alerts, or non-Sentry error monitoring.
Best use case
sentry is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Inspect Sentry issues, summarize production errors, and pull health data via the Sentry API (read-only). Use when user says "check Sentry", "what errors in production?", "summarize Sentry issues", "recent crashes", or "production error report". Requires SENTRY_AUTH_TOKEN. Do NOT use for setting up Sentry SDK, configuring alerts, or non-Sentry error monitoring.
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
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/sentry/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How sentry Compares
| Feature / Agent | sentry | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Inspect Sentry issues, summarize production errors, and pull health data via the Sentry API (read-only). Use when user says "check Sentry", "what errors in production?", "summarize Sentry issues", "recent crashes", or "production error report". Requires SENTRY_AUTH_TOKEN. Do NOT use for setting up Sentry SDK, configuring alerts, or non-Sentry error monitoring.
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.
## Skill path (set once)
```bash
export AGENT_SKILLS_HOME="${AGENT_SKILLS_HOME:-$HOME/.agent-skills}"
export SENTRY_API="$AGENT_SKILLS_HOME/skills/sentry/scripts/sentry_api.py"
```
User-scoped skills install under `$AGENT_SKILLS_HOME/skills` (default: `~/.agent-skills/skills`).
### 1) List issues (ordered by most recent)
```bash
python3 "$SENTRY_API" \
list-issues \
--org {your-org} \
--project {your-project} \
--environment prod \
--time-range 24h \
--limit 20 \
--query "is:unresolved"
```
### 2) Resolve an issue short ID to issue ID
```bash
python3 "$SENTRY_API" \
list-issues \
--org {your-org} \
--project {your-project} \
--query "ABC-123" \
--limit 1
```
Use the returned `id` for issue detail or events.
### 3) Issue detail
```bash
python3 "$SENTRY_API" \
issue-detail \
1234567890
```
### 4) Issue events
```bash
python3 "$SENTRY_API" \
issue-events \
1234567890 \
--limit 20
```
### 5) Event detail (no stack traces by default)
```bash
python3 "$SENTRY_API" \
event-detail \
--org {your-org} \
--project {your-project} \
abcdef1234567890
```
## API requirements
Always use these endpoints (GET only):
- List issues: `/api/0/projects/{org_slug}/{project_slug}/issues/`
- Issue detail: `/api/0/issues/{issue_id}/`
- Events for issue: `/api/0/issues/{issue_id}/events/`
- Event detail: `/api/0/projects/{org_slug}/{project_slug}/events/{event_id}/`
## Inputs and defaults
- `org_slug`, `project_slug`: default to `{your-org}`/`{your-project}` (avoid non-prod orgs).
- `time_range`: default `24h` (pass as `statsPeriod`).
- `environment`: default `prod`.
- `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.”
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