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.

MyTT将通达信,同花顺,文华麦语言等指标公式,最简移植到Python中,核心库单个文件，仅百行代码,十几个核心函数，神奇的实现所有常见技术指标算法（不依赖talib库）的纯python实现和转换通达信MACD,RSI,BOLL,ATR,KDJ,CCI,PSY等公式,全部基于pandas函数计算方法封装，简洁且高性能，能非常方便的应用在股票指标公式,股市期货量化框架分析,自动程序化交易,数字货币量化等领域,它是您最精练的股市量化工具。Python library with most stock market indicators.

01Result

mpquant/MyTT ↗

mpquant/MyTT AI coding statistics: 0%

of 1 commits in February–September 15, 2026 were committed by an AI agent — a floor, not an estimate

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

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 mpquant/MyTT

Scan another repository

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