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.

一套为研究生和学术研究者设计的完整AI Prompt库 📖 包含内容： ✨ 40+ 精心设计的AI Prompt ✨ 论文选题系统方法（生成、评估、论证） ✨ 论文查找快速方案（8个不同方案） ✨ 文献综述框架和工具 ✨ Excel自动评估表格 ✨ 3个完整的论证模板 🚀 核心优势： ⚡ 节省时间 50-70%（选题3-5天而不是2-3周） 🎯 科学方法（基于系统的5维度评估体系） 💡 即插即用（所有Prompt直接复制可用） 📚 全流程覆盖（从选题到出版的完整方案） 🎓 适用人群： 👨‍🎓 硕士研究生 | 博士研究生 | 本科毕业设计 | 学术研究者 | 内容创作者

01Result

bohyy/academic-ai-prompt ↗

bohyy/academic-ai-prompt AI coding statistics: 0%

of 30 commits in February–September 15, 2026 were committed by an AI agent — a floor, not an estimate

Too little recent activity to publish. Only 30 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 30 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	30
Merge commits removed	−0
CI / dependency bots removed	−0
Considered	30

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

Continue exploring

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 bohyy/academic-ai-prompt

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