From the experiment

Do coding agents recommend Checkly?

Checkly was chosen in 5% of 360 judged observability sessions, ranking fourth. Measured with Claude Code, Codex and Cursor.

Published September 3, 2026 Read as Markdown

Checkly was chosen in 5% of 360 judged observability sessions, ranking fourth. It was also raised as a candidate in 15 further sessions without being chosen.

This page reports what happened when Claude Code, Codex and Cursor had to solve a problem in observability inside a realistic codebase. Not what a chat assistant says about Checkly. What an agent actually installed.

The numbers

CategoryObservability
Sessions in the category360
Sessions where Checkly was chosen17
Install share5%
Rank in category4 of 16
Codebases it won in3
Raised as a candidate, not chosen15
Chosen when considered53%
Sitechecklyhq.com

By agent

With 17 wins spread across three agents, the rates below are small numbers and a difference between them is not yet a finding. They are here because the direction is worth knowing, not because the gap is established.

AgentSessionsChose ChecklyShare
Claude Code12011%
Codex1201210%
Cursor12043%

By who was asking

Checkly performs similarly across the four kinds of buyer, from 0% to 6%. That is unusual: the category leader changed with the persona in 14 of the 18 categories we measured.

Who is askingSessionsChose ChecklyShare
Vibe coder1200%
Junior developer1200%
Senior engineer300176%
Enterprise team3600%

What Checkly was up against

The full ranking in observability, from the same sessions:

#ProductRuns wonShare
1Sentry13337%
2Grafana5214%
3Amazon CloudWatch308%
4Built in-house (no product adopted)226%
5Checkly (this page)175%
6Datadog164%
7Better Stack154%
8New Relic154%

What this means

Agents almost never raise Checkly without choosing it: 15 sessions raised against 17 chosen. When it gets considered, it usually wins. The constraint is how rarely it gets considered at all, which is a presence problem: templates, framework integrations and pages that answer the configuration and production questions agents actually search for.

Where these numbers come from

The 360 sessions in observability are part of a published set of 5,292, run with real coding agents inside realistic codebases and judged blind. The full method is on one page: how we measured this.

Every observability run can be replayed on the board.

If you work on Checkly: the judge recorded a reason for every session where it was raised and passed over. Those reasons are in the transcripts.

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Common questions

Do coding agents recommend Checkly?

Yes. Checkly was chosen in 17 of the 360 judged sessions in observability, a 5% install share, ranking fourth in its category.

Does Claude Code recommend Checkly?

In 1 of the 120 sessions in observability run with Claude Code, which is 1%.

Do different coding agents treat Checkly differently?

Not much. The three agents chose it at similar rates, between 1% and 10% of their runs.

How was this measured?

Real coding agents at pinned versions were run in sandboxes inside 51 realistic codebases and asked to solve real tasks. A simulated project owner approved or questioned each recommendation before any code was written, and a judge from a model family that builds none of the agents read every session blind.

How often is Checkly considered but not chosen?

It was raised as a candidate in 15 sessions without being chosen, and chosen in 17. That is a 53% conversion from considered to chosen.

Where this comes from

Armature ran 5,292 judged sessions with Claude Code, Codex and Cursor inside 51 realistic codebases, and published every run. The numbers on this page come from that work.

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