Dataset: 2026-10-27-catalog-ai-v2
Ruleset: b2e8889c66f7
Scanned: 2026-10-27
Window: February–September 15, 2026

Catalog tracking observation. This repository is measured with the same fixed window and ruleset, but it is not part of the published benchmark or its aggregate claims.

JEECG是一款基于代码生成器的J2EE快速开发平台，开源界“小普元”超越传统商业企业级开发平台。引领新的开发模式(Online Coding模式(自定义表单) - > 代码生成器模式 - > 手工MERGE智能开发)，可以帮助解决Java项目90%的重复工作，让开发更多关注业务逻辑。既能快速提高开发效率，帮助公司节省人力成本，同时又不失灵活性。具备：表单配置能力（无需编码）、移动配置能力、工作流配置能力、报表配置能力（支持移动端）、插件开发能力（可插拔）

01Result

jeecgboot/jeecg ↗

jeecgboot/jeecg AI coding statistics: 0%

of 0 commits in February–September 15, 2026 were committed by an AI agent — a floor, not an estimate

Too little recent activity to publish. Only 0 commits landed in this window, so the percentage is noisy. Repositories below 100 are excluded from the index for this reason.

No signed agent commits found

No agent signatures were found in the last 0 considered commits. That is a real result, not a failure to measure.

It does not mean no AI was used here. A developer can use an agent and commit by hand without leaving a detectable git signature.

agent commits

other considered commits

—

agent contributors

—

largest contributor

02Drivers

What shapes this result

Mode, timing, and detected signatures show whether the result reflects broad adoption or one concentrated workflow.

No agent signatures were detected, so there are no agent, mode, or timing drivers to break down.

03Evidence

Inspect the matches

Public commit samples let you inspect the signatures behind the aggregate result.

No matched commit samples are available for this observation.

04Method

What entered the denominator

The result begins with commit history, removes merges and routine automation, and reports literal agent signatures as a lower bound.

Exclusion ledger

Commits in window	0
Merge commits removed	−0
CI / dependency bots removed	−0
Considered	0

Bots are excluded from the denominator entirely. Agent attribution requires a literal supported signature; no code-style inference is used.

Continue exploring

Java AI coding statisticsCompare evidence across Java repositories →GitHub AI commit analyzerInspect another repository with the same evidence model →

Reproduce this observation

Run the same detector locally.

Deterministic signature matching; no code-style inference. Squash merges can remove trailers, so this result remains a measured floor.

npx qmmit-cli jeecgboot/jeecg

Scan another repository

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