<!-- skill: sentry | version: 1.0.0 | updated: 2026-03-17 -->

---

Best use case

<!-- skill: sentry | version: 1.0.0 | updated: 2026-03-17 --> is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

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Teams using <!-- skill: sentry | version: 1.0.0 | updated: 2026-03-17 --> 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/guilhermemarketing/esc-skills/main/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 <!-- skill: sentry | version: 1.0.0 | updated: 2026-03-17 --> Compares

Feature / Agent<!-- skill: sentry | version: 1.0.0 | updated: 2026-03-17 -->Standard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

---

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

<!-- skill: sentry | version: 1.0.0 | updated: 2026-03-17 -->
---
name: sentry
description: 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`.
metadata:
  author: github.com/openai/skills
  version: '1.0.0'
---

# 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.”
Expected: ordered list with titles, short IDs, counts, last seen.