From the experiment

Do coding agents recommend Leaflet?

Leaflet was chosen in 16% of 319 judged maps sessions, ranking second. Measured with Claude Code, Codex and Cursor.

Published September 11, 2026 Read as Markdown

Leaflet was chosen in 16% of 319 judged maps sessions, ranking second. It was also raised as a candidate in 158 further sessions without being chosen.

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

The numbers

CategoryMaps
Sessions in the category319
Sessions where Leaflet was chosen52
Install share16%
Rank in category2 of 32
Codebases it won in7
Raised as a candidate, not chosen158
Chosen when considered25%
Siteleafletjs.com

By agent

The three agents treat Leaflet very differently. Cursor chose it in 30% of its sessions in this category and Claude Code in 10%, a spread of 20 points.

AgentSessionsChose LeafletShare
Claude Code1081110%
Codex1111110%
Cursor1003030%

A single blended install share would report the midpoint and hide both ends. If most of your users run Claude Code, your real position here is 10%, not 16%.

By who was asking

Leaflet does much better with one kind of buyer than another. It won 20% of sessions asked as vibe coder and 0% of those asked as enterprise team.

Who is askingSessionsChose LeafletShare
Vibe coder641320%
Junior developer1472920%
Senior engineer721014%
Enterprise team3600%

What Leaflet was up against

The full ranking in maps, from the same sessions:

#ProductRuns wonShare
1Google Maps5216%
2Leaflet (this page)5216%
3Apple Maps (MapKit)4614%
4Mapbox258%
5MapLibre217%
6react-native-maps196%
7Azure Maps186%
8Built in-house (no product adopted)165%

What this means

A solid second or third position in a category means the agent is genuinely choosing rather than reaching automatically. That is a winnable position, because the inputs it uses can be changed.

The fastest gains are usually in the sessions that were nearly won: read them, find the step where the agent moved on, and fix that step.

Where these numbers come from

The 319 sessions in maps are part of a published set of 6,458, run with real coding agents inside realistic codebases and judged blind. The full method is on one page: how we measured this.

Every maps run can be replayed on the board.

If you work on Leaflet: 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 Leaflet?

Yes. Leaflet was chosen in 52 of the 319 judged sessions in maps, a 16% install share, ranking second in its category.

Does Claude Code recommend Leaflet?

In 11 of the 108 sessions in maps run with Claude Code, which is 10%.

Do different coding agents treat Leaflet differently?

Yes, and by a wide margin. Cursor chose it in 30% of its runs and Claude Code in 10%.

How was this measured?

Real coding agents at pinned versions were run in sandboxes inside 63 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 Leaflet considered but not chosen?

It was raised as a candidate in 158 sessions without being chosen, and chosen in 52. That is a 25% conversion from considered to chosen.

Where this comes from

Armature ran 6,458 judged sessions with Claude Code, Codex and Cursor inside 63 realistic codebases, and published every run. The numbers on this page come from that work.

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