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.

一个面向workbuddy / Codex 等agent 的跨境电商和国内电商通用视觉创作 Skill。我精选25个高质量案例，涵盖纯色底产品主图、场景化生活图、平铺图、电商详情图、真实场景等等，全部配完整提示词，都可以利用 GPT-Image-2 API生成最终效果。一键生成电商相关图片！输入产品图片和需求描述，自动生成完整的电商主图、详情页图片、社媒推广图、直播间场景图等全套视觉素材。与众不同之处是：**Campaign Style Lock** 机制和 **强推广** 和 **重视转化效果**。

01Result

liangdabiao/ecom-details-image ↗

liangdabiao/ecom-details-image AI coding statistics: 0%

of 13 commits in February–September 15, 2026 were committed by an AI agent — a floor, not an estimate

Too little recent activity to publish. Only 13 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 13 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	14
Merge commits removed	−1
CI / dependency bots removed	−0
Considered	13

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

Continue exploring

Python AI coding statisticsCompare evidence across Python 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 liangdabiao/ecom-details-image

Scan another repository

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