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openai/sentry

openai

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 CLI; perform read-only queries using the `sentry` command.

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v2.0Saved Apr 20, 2026

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.

Files4
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Overall Score

81/100

Grade

B

Good

Safety

82

Quality

78

Clarity

85

Completeness

76

Summary

A read-only Sentry observability skill that enables AI agents to inspect production issues, summarize recent errors, and pull health data via the Sentry CLI. The skill provides guidance for listing issues, viewing event details, and using AI-powered root cause analysis — all without modifying Sentry data.

Static Analysis Findings

3 findings

Patterns detected by deterministic static analysis before AI scoring. Hover over any finding code for detailed information and remediation guidance.

Credential Exposure
SEC-020Direct .env File Access

Direct .env file access

SKILL.md.env
Command Injection
SEC-010Pipe-to-ShellMax: B

Pipe-to-shell pattern (curl/wget piped to sh/bash)

SKILL.mdcurl https://cli.sentry.dev/install -fsS | bash
Network Access
SEC-060Outbound Network Request

Outbound network request (curl/wget/fetch)

SKILL.mdcurl https://

Detected Capabilities

Execute Sentry CLI commands for read-only queriesAuto-detect org/project from environment and source codeParse JSON output from Sentry APIQuery issues with filters (environment, status, date range)Invoke AI-powered root cause and fix planning toolsAccess Sentry schema to discover API endpoints

Trigger Keywords

Phrases that MCP clients use to match this skill to user intent.

investigate sentry issuecheck production errorssentry root causeanalyze error spikequery unresolved issuessentry event detailsproduction observabilityerror trend analysis

Risk Signals

WARNING

SEC-010: Pipe-to-shell installation command

SKILL.md | Line: Installation step 1
INFO

SEC-020: Direct .env file access reference

SKILL.md | Line: Quick start and section 1
INFO

SEC-060: Outbound network requests (Sentry API calls)

SKILL.md | Lines: Core tasks and fallback API access

Referenced Domains

External domains referenced in skill content, detected by static analysis.

cli.sentry.devwww.apache.org

Use Cases

  • Investigate production errors and summarize recent issues
  • Retrieve root cause analysis for unresolved bugs
  • Query issue details by short ID or event ID
  • Pull health metrics and error trends for a specific time period
  • Discover available Sentry API endpoints

Quality Notes

  • ✓ Clear scope boundary: the skill is explicitly read-only and does not modify Sentry data
  • ✓ Security-conscious instructions: skill explicitly advises against pasting tokens in chat and recommends local environment setup
  • ✓ Well-documented CLI usage: all seven core tasks include example commands with flags and output expectations
  • ✓ Sensible defaults documented: time range (24h), environment (production), and limit (20 results) are clearly stated
  • ✓ Output formatting rules provided: includes guidance on what to display, PII redaction, and error handling
  • ✓ Golden test inputs section aids verification and debugging
  • ✓ Fallback API access section extends coverage beyond dedicated CLI commands
  • ⚠ No error handling guidance: skill does not describe how to handle authentication failures, network timeouts, or empty result sets
  • ⚠ No explicit limitations on API rate limits or large result sets: skill should warn about pagination and data volume
  • ⚠ Auto-detection complexity not fully detailed: the skill mentions org/project auto-detection but does not explain the search order or fallback behavior in depth
Model: claude-haiku-4-5-20251001Analyzed: Apr 20, 2026

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Version History

v2.0

Contract changed: description

2026-04-20

Latest
v1.0

Seeded from github.com/openai/skills

2026-03-16

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