- Dataset
- 2026-10-27-catalog-ai-v2
- Ruleset
- b2e8889c66f7
- Scanned
- 2026-10-27
- Window
- February–September 15, 2026
良心的 Python 教程,面向零基础初学者简明易懂的 Python3 入门基础课程。在linux+vim生产力环境下,从浅入深,从简单程序学到网络爬虫。可以配合蓝桥云上实验环境操作。
01Result
overmind1980/oeasy-python-tutorial ↗overmind1980/oeasy-python-tutorial AI coding statistics: 0%
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.
02Drivers
What shapes this result
Mode, timing, and detected signatures show whether the result reflects broad adoption or one concentrated workflow.
03Evidence
Inspect the matches
Public commit samples let you inspect the signatures behind the aggregate result.
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 | 13 |
| Merge commits removed | −0 |
| 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
Related coding-agent evidence
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 overmind1980/oeasy-python-tutorial