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.

(vue.js official website tutorials ，contains video , codes, baudi yun, youtube) 网路上有很多 VUE 综合应用的视频，但大部份的视频，都当你已经了解官网所以讲的节奏难免偏快。此视频(都是上代码)，以官网为重，将官网的观念，以视频搭配代码，实际演示。如果官网有看不懂的地方，比对一下，视频跟代码，就会了解了。减少你摸索的时间。(註：mvvm 的框架，不管是 ng , react, vue, avalonjs, 都是好的框架，而有经验的前端，至少都会两套以上的 mvvm。)

01Result

bhnddowinf/vuejs-learn ↗

bhnddowinf/vuejs-learn 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

JavaScript AI coding statisticsCompare evidence across JavaScript 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 bhnddowinf/vuejs-learn

Scan another repository

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