Report card

Do AI agents pick Sentry?

How often agents choose Sentry when a developer needs error monitoring — measured across Claude, GPT, Gemini.

Sentry

#1 of 6 observability
60%Pick Rate
95% CI 53%66%

When developers ask an AI agent for observability, Sentry is picked 60% of the time — ranking #1 of 6 measured across Claude, GPT, Gemini.

Picked 60% Named, not picked 30% Never surfaced 10%

Top pick in the category. 🟢

Awareness

34.1M package downloads / week

Strong presence, and agents pick you.

0 docs in FineWeb (10BT sample) · 716 URLs in Common Crawl

In the raw web crawl, but thin in the filtered corpus models actually train on — an awareness gap at the source.

AdoptionDid the pick convert to installs? Public Adoption = npm downloads of your packages. The proof half of the funnel.

301.2M installs / month ▲ 11% MoM

Picks are converting — installs are climbing alongside a healthy Pick Rate.

Get the full report

The per-model and per-surface breakdown for Sentry — where it wins, where it loses, and to whom — plus an alert when the Pick Rate moves.

About Sentry

Application monitoring platform for tracking errors and performance in production software.

Sentry captures errors, exceptions, and performance data from running applications, giving developers visibility into what's breaking and why. It supports a wide range of languages and frameworks, with the Node.js SDK using OpenTelemetry under the hood for performance instrumentation. It's aimed at development teams who need to detect, triage, and fix issues in production.

Where to start

Install the Node SDK, create an instrument.js file that calls Sentry.init() with your DSN, and load it before any other modules in your application. For ESM projects, use the Node.js --import flag to ensure Sentry initializes before application code runs.

Install

Links and summary verified from public sources.

The rest of the Error Monitoring ranking

← Full Error Monitoring leaderboard · How this is measured