Warden

Warden is an AI-powered code review tool from Sentry. It "watches over your code by running skills against your changes" — analyzing diffs, files, or whole branches for security issues, API problems, performance regressions, and any custom patterns a team cares about. Warden runs both locally (pre-p

Canonical version: Warden.

Warden is an AI-powered code review tool from Sentry. It "watches over your code by running skills against your changes" — analyzing diffs, files, or whole branches for security issues, API problems, performance regressions, and any custom patterns a team cares about. Warden runs both locally (pre-push) and in CI (on pull requests).

It is distributed via npm as @sentry/warden and the source is at getsentry/warden. License: FSL-1.1-ALv2.

The Core Idea: Skills as the Unit of Review

Where a traditional linter has hard-coded rules, Warden review logic is expressed as skills — markdown files following the AI Agent Skills specification (the same spec Claude Code Skills uses). Each skill has YAML frontmatter and a natural-language prompt describing what to look for, success criteria, and concrete examples.

Skills live in conventional directories (.agents/skills/ or .claude/skills/) so they're shared with other agentic tools. Define analysis once, run it via Warden, Claude Code, or any agentskills-compliant runner.

This is the same insight behind AI Skill Composability and AI Skill Portability — review logic is just a skill, and skills compose.

Workflow

  1. Detect changes — modified files, hunks, or directories
  2. Match triggers — compare alterations against configured skills
  3. Run analysis — execute relevant skills, report findings with severity, optionally suggest or auto-apply fixes

Findings appear inline as PR comments on GitHub, or in the terminal locally.

Configuration

warden.toml at the repository root declares:

  • Which skills to run (local paths or getsentry/warden-skills-style remote refs)
  • Path globs (paths, ignorePaths)
  • Severity thresholds (failOn, reportOn) — critical / high / medium / low / info / off
  • Triggers (pull_request, local, schedule)
  • Defaults (model, max turns per hunk — default 50, auxiliary/synthesis models)
  • Chunking strategy (per-hunk, whole-file, skip)

Comparison with Vercel DeepSec

Both are AI-agent code review tools but target different shapes of work:

Warden Vercel DeepSec
Built by Sentry Vercel Labs
Primary scope Diffs, PRs, pre-commit Whole-codebase deep audits
Speed Fast, runs on every push Slow, hours per scan
Cost Per-PR, low Thousands per scan
Pipeline Single skill per chunk 5-stage agent pipeline
Output PR comments Tickets / markdown reports

In practice they're complementary: DeepSec finds the dormant bugs already in your codebase; Warden keeps new ones from being added.

Authentication

  • Local: claude login (uses your Claude Code subscription) or WARDEN_ANTHROPIC_API_KEY / ANTHROPIC_API_KEY
  • CI: organization secret WARDEN_ANTHROPIC_API_KEY plus a custom GitHub App via warden setup-app

The companion repo getsentry/warden-skills ships generalized skills (security, performance, API hygiene). Add them with warden add --remote getsentry/warden-skills --skill <skill-name>. Pin to a ref for reproducibility. Update with warden sync getsentry/warden-skills.

References


About Sébastien

I'm Sébastien Dubois, and I'm on a mission to help knowledge workers escape information overload. After 20+ years in IT and seeing too many brilliant minds drowning in digital chaos, I've decided to help people build systems that actually work. Through the Knowii Community, my courses, products & services and my Website/Newsletter, I share practical and battle-tested systems.

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