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.

Python AutoML toolkit for benchmarking classification, regression, and time-series forecasting models, with GPU acceleration, MLflow tracking, and automated preprocessing.

01Result

shankarpandala/lazypredict ↗

shankarpandala/lazypredict AI coding statistics: 97.8%

of 45 commits in February–September 15, 2026 were committed by an AI agent — a floor, not an estimate

Too little recent activity to publish. Only 45 commits landed in this window, so the percentage is noisy. Repositories below 100 are excluded from the index for this reason.

97.8% agent · top contributor 79.5%3 contributors

individual

One person is driving this. The headline number reflects a single contributor's workflow, not a project-wide shift.

agent commits

other considered commits

agent contributors

79.5%

largest contributor

02Drivers

What shapes this result

Mode, timing, and detected signatures show whether the result reflects broad adoption or one concentrated workflow.

Assisted or autonomous

44assisted

0autonomous

Assisted — a developer’s identity authored the commit and the agent added itself as co-author. Autonomous — a bot identity authored the commit without a human identity attached.

Agent share by month

Peak month: 100%. Bars are scaled to that peak, not to 100%.

Which agents

Agent	Vendor	Commits	Share
Claude Code	Anthropic	42	93.3%
GitHub Copilot	GitHub	2	4.4%

03Evidence

Inspect the matches

Public commit samples let you inspect the signatures behind the aggregate result.

Matched commit samples

659bcbbf on GitHubPublish docs from dev until dev→master is caught upClaude Code
99b6bd26 on GitHubPublish per-PR docs previews to GitHub PagesClaude Code
181df700 on GitHubBuild docs on push to dev and on ready_for_review eventsClaude Code
28814906 on GitHubdocs: comprehensive documentation updateGitHub Copilot
32488710 on GitHubchore: remove myst-parser sphinx leftover from requirements_devGitHub Copilot

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	65
Merge commits removed	−16
CI / dependency bots removed	−4
Considered	45

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

Continue exploring

Claude Code commitsBrowse repositories with detected Claude Code signatures →GitHub Copilot commitsBrowse repositories with detected GitHub Copilot signatures →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 shankarpandala/lazypredict

Scan another repository

Try

Month	Agent share	Considered commits
2026-03	97.1%	35
2026-04	100%	10