sentry-cli

sentry/dev · updated Apr 8, 2026

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$npx skills add https://github.com/sentry/dev --skill sentry-cli
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summary

Command-line interface for querying and managing Sentry issues, projects, organizations, and distributed traces.

  • Supports 15+ command categories: authentication, organizations, projects, issues, events, dashboards, repositories, teams, logs, spans, traces, and API calls
  • Includes AI-powered issue analysis via sentry issue explain and sentry issue plan using Seer AI
  • Offers JSON output for all major commands, enabling easy integration with scripts and tools
  • Provides flexible project
skill.md

Sentry CLI Usage Guide

Help users interact with Sentry from the command line using the sentry CLI.

Agent Guidance

Best practices and operational guidance for AI coding agents using the Sentry CLI.

Key Principles

  • Just run the command — the CLI handles authentication and org/project detection automatically. Don't pre-authenticate or look up org/project before running commands. If auth is needed, the CLI prompts interactively.
  • Prefer CLI commands over raw API calls — the CLI has dedicated commands for most tasks. Reach for sentry issue view, sentry issue list, sentry trace view, etc. before constructing API calls manually or fetching external documentation.
  • Use sentry schema to explore the API — if you need to discover API endpoints, run sentry schema to browse interactively or sentry schema <resource> to search. This is faster than fetching OpenAPI specs externally.
  • Use sentry issue view <id> to investigate issues — when asked about a specific issue (e.g., CLI-G5, PROJECT-123), use sentry issue view directly.
  • Use --json for machine-readable output — pipe through jq for filtering. Human-readable output includes formatting that is hard to parse.
  • The CLI auto-detects org/project — most commands work without explicit targets by scanning for DSNs in .env files, source code, config defaults, and directory names. Only specify <org>/<project> when the CLI reports it can't detect the target or detects the wrong one.

Design Principles

The sentry CLI follows conventions from well-known tools — if you're familiar with them, that knowledge transfers directly:

  • gh (GitHub CLI) conventions: The sentry CLI uses the same <noun> <verb> command pattern (e.g., sentry issue list, sentry org view). Flags follow gh conventions: --json for machine-readable output, --fields to select specific fields, -w/--web to open in browser, -q/--query for filtering, -n/--limit for result count.
  • sentry api mimics curl: The sentry api command provides direct API access with a curl-like interface — --method for HTTP method, --data for request body, --header for custom headers. It handles authentication automatically. If you know how to call a REST API with curl, the same patterns apply.

Context Window Tips

  • Use --json --fields to select specific fields and reduce output size. Run <command> --help to see available fields. Example: sentry issue list --json --fields shortId,title,priority,level,status
  • Use --json when piping output between commands or processing programmatically
  • Use --limit to cap the number of results (default is usually 10–100)
  • Prefer sentry issue view PROJECT-123 over listing and filtering manually
  • Use sentry api for endpoints not covered by dedicated commands

Safety Rules

  • Always confirm with the user before running destructive commands: project delete, trial start
  • For mutations, verify the org/project context looks correct in the command output before proceeding with further changes
  • Never store or log authentication tokens — the CLI manages credentials automatically
  • If the CLI reports the wrong org/project, override with explicit <org>/<project> arguments

Workflow Patterns

Investigate an Issue

# 1. Find the issue (auto-detects org/project from DSN or config)
sentry issue list --query "is:unresolved" --limit 5

# 2. Get details
sentry issue view PROJECT-123

# 3. Get AI root cause analysis
sentry issue explain PROJECT-123

# 4. Get a fix plan
sentry issue plan PROJECT-123

Explore Traces and Performance

# 1. List recent traces (auto-detects org/project)
sentry trace list --limit 5

# 2. View a specific trace with span tree
sentry trace view abc123def456...

# 3. View spans for a trace
sentry span list abc123def456...

# 4. View logs associated with a trace
sentry trace logs abc123def456...

Stream Logs

# Stream logs in real-time (auto-detects org/project)
sentry log list --follow

# Filter logs by severity
sentry log list --query "severity:error"

Explore the API Schema

# Browse all API resource categories
sentry schema

# Search for endpoints related to a resource
sentry schema issues

# Get details about a specific endpoint
sentry schema "GET /api/0/organizations/{organization_id_or_slug}/issues/"

Arbitrary API Access

# GET request (default)
sentry api /api/0/organizations/my-org/

# POST request with data
sentry api /api/0/organizations/my-org/projects/ --method POST --data '{"name":"new-project","platform":"python"}'

Dashboard Layout

Sentry dashboards use a 6-column grid. When adding widgets, aim to fill complete rows (widths should sum to 6).

Display types with default sizes:

Display Type Width Height Category Notes
big_number 2 1 common Compact KPI — place 3 per row (2+2+2=6)
line 3 2 common Half-width chart — place 2 per row (3+3=6)
area 3 2 common Half-width chart — place 2 per row
bar 3 2 common Half-width chart — place 2 per row
table 6 2 common Full-width — always takes its own row
stacked_area 3 2 specialized Stacked area chart
top_n 3 2 specialized Top N ranked list
categorical_bar 3 2 specialized Categorical bar chart
text 3 2 specialized Static text/markdown widget
details 3 2 internal Detail view
wheel 3 2 internal Pie/wheel chart
rage_and_dead_clicks 3 2 internal Rage/dead click visualization
server_tree 3 2 internal Hierarchical tree display
agents_traces_table 3 2 internal Agents traces table

Use common types for general dashboards. Use specialized only when specifically requested. Avoid internal types unless the user explicitly asks.

Available datasets: spans (default), tracemetrics, discover, issue, error-events, logs. Run sentry dashboard widget --help for dataset descriptions, query formats, and examples.

Row-filling examples:

# 3 KPIs filling one row (2+2+2 = 6)
sentry dashboard widget add <dashboard> "Error Count" --display big_number --query count
sentry dashboard widget add <dashboard> "P95 Duration" --display big_number --query p95:span.duration
sentry dashboard widget add <dashboard> "Throughput" --display big_number --query epm

# 2 charts filling one row (3+3 = 6)
sentry dashboard widget add <dashboard> "Errors Over Time" --display line --query count
sentry dashboard widget add <dashboard> "Latency Over Time" --display line --query p95:span.duration

# Full-width table (6 = 6)
sentry dashboard widget add <dashboard> "Top Endpoints" --display table \
  --query count --query p95:span.duration \
  --group-by transaction --sort -count --limit 10

Quick Reference

Time filtering

Use --period (alias: -t) to filter by time window:

sentry trace list --period 1h
sentry span list --period 24h
sentry span list -t 7d

Scoping to an org or project

Org and project are positional arguments following gh CLI conventions:

sentry trace list my-org/my-project
sentry issue list my-org/my-project
sentry span list my-org/my-project/abc123def456...

Listing spans in a trace

Pass the trace ID as a positional argument to span list:

sentry span list abc123def456...
sentry span list my-org/my-project/abc123def456...

Dataset names for the Events API

When querying the Events API (directly or via sentry api), valid dataset values are: spans, transactions, logs, errors, discover.

Release Workflow

The sentry release command group manages Sentry releases for tracking deploys and associating commits with errors. A typical CI workflow:

# Create a release (version must match Sentry.init() release value)
sentry release create my-org/1.0.0 --project my-project

# Associate commits via repository integration (requires git checkout)
sentry release set-commits my-org/1.0.0 --auto

# Mark the release as finalized
sentry release finalize my-org/1.0.0

# Record a deploy
sentry release deploy my-org/1.0.0 production

Key details:

  • The org/version positional is <org-slug>/<version>, NOT a version prefix. sentry release create sentry/1.0.0 means org=sentry, version=1.0.0. This is how org is specified — not via SENTRY_ORG.
  • The release version (e.g., 1.0.0) must match the release value in your Sentry.init() call. If your SDK uses bare semver, the release must be bare semver too.
  • --auto requires both a Sentry repository integration (GitHub/GitLab/Bitbucket) and a local git checkout. It lists repos from the API and matches against your local origin remote URL, then sends the HEAD commit SHA. Without a checkout, use --local instead.
  • When neither --auto nor --local is specified, the CLI tries --auto first and falls back to --local on failure.

CI/CD Setup Notes

  • The sentry npm package requires Node.js >= 22. CI runners like ubuntu-latest ship Node.js 20 — add actions/setup-node@v6 with node-version: 22.
  • If SENTRY_AUTH_TOKEN is scoped to a GitHub environment (e.g., production), set environment: production on the job.
  • A full git checkout (fetch-depth: 0) is needed for --auto to discover the remote URL and HEAD.
  • set-commits --auto has continue-on-error in most workflows because it requires a working repository integration. If the integration isn't configured, the step fails but the rest of the release workflow succeeds.

Common Mistakes

  • Wrong issue ID format: Use PROJECT-123 (short ID), not the numeric ID 123456789. The short ID includes the project prefix.
  • Pre-authenticating unnecessarily: Don't run sentry auth login before every command. The CLI detects missing/expired auth and prompts automatically. Only run sentry auth login if you need to switch accounts.
  • Missing --json for piping: Human-readable output includes formatting. Use --json when parsing output programmatically.
  • Specifying org/project when not needed: Auto-detection resolves org/project from DSNs, env vars, config defaults, and directory names. Let it work first — only add <org>/<project> if the CLI says it can't detect the target or detects the wrong one.
  • Confusing --query syntax: The --query flag uses Sentry search syntax (e.g., is:unresolved, assigned:me), not free text search.
  • Not using --web: View commands support -w/--web to open the resource in the browser — useful for sharing links.
  • Fetching API schemas instead of using the CLI: Prefer sentry schema to browse the API and sentry api to make requests — the CLI handles authentication and endpoint resolution, so there's rarely a need to download OpenAPI specs separately.
  • Release version mismatch: The org/version positional is <org-slug>/<version>, where org/ is the org, not part of the version. sentry release create sentry/1.0.0 creates version 1.0.0 in org sentry. If your Sentry.init() uses release: "1.0.0", this is correct. Don't double-prefix like sentry/myapp/1.0.0.
  • Running set-commits --auto without a git checkout: --auto needs a local git repo to discover the origin remote URL and HEAD commit. In CI, ensure actions/checkout with fetch-depth: 0 runs before set-commits --auto.
  • Using sentry api when CLI commands suffice: sentry issue list --json already includes shortId, title, priority, level, status, permalink, and other fields at the top level. Some fields like count, userCount, firstSeen, and lastSeen may be null depending on the issue. Use --fields to select specific fields and --help to see all available fields. Only fall back to sentry api for data the CLI doesn't expose.

Prerequisites

The CLI must be installed and authenticated before use.

Installation

curl https://cli.sentry.dev/install -fsS | bash
curl https://cli.sentry.dev/install -fsS | bash -s -- --version nightly

# Or install via npm/pnpm/bun
npm install -g sentry

Authentication

sentry auth login
sentry auth login --token YOUR_SENTRY_API_TOKEN
sentry auth status
sentry auth logout

Command Reference

Auth

Authenticate with Sentry

  • sentry auth login — Authenticate with Sentry
  • sentry auth logout — Log out of Sentry
  • sentry auth refresh — Refresh your authentication token
  • sentry auth status — View authentication status
  • sentry auth token — Print the stored authentication token
  • sentry auth whoami — Show the currently authenticated user

→ Full flags and examples: references/auth.md

Org

Work with Sentry organizations

  • sentry org list — List organizations
  • sentry org view <org> — View details of an organization
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how to use sentry-cli

How to use sentry-cli on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add sentry-cli
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/sentry/dev --skill sentry-cli

The skills CLI fetches sentry-cli from GitHub repository sentry/dev and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/sentry-cli

Reload or restart Cursor to activate sentry-cli. Access the skill through slash commands (e.g., /sentry-cli) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.628 reviews
  • Daniel Dixit· Sep 17, 2024

    sentry-cli has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Sakshi Patil· Sep 13, 2024

    Solid pick for teams standardizing on skills: sentry-cli is focused, and the summary matches what you get after install.

  • Omar Khanna· Sep 13, 2024

    Registry listing for sentry-cli matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Harper Thomas· Sep 1, 2024

    sentry-cli fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Noah Kapoor· Aug 20, 2024

    sentry-cli has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Nia Taylor· Aug 8, 2024

    sentry-cli fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Chaitanya Patil· Aug 4, 2024

    I recommend sentry-cli for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Diya Sharma· Aug 4, 2024

    Useful defaults in sentry-cli — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Diya Kapoor· Jul 27, 2024

    I recommend sentry-cli for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Piyush G· Jul 23, 2024

    sentry-cli fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

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