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.

Claude skills for LinkedIn. 12 Claude Code and Codex skills that write human-sounding LinkedIn posts, craft comments that get noticed, analyze your feed, and build a publishing cadence, all from your terminal. Content engineering by Creative Content Crafts. MIT.

01Result

sergebulaev/linkedin-skills ↗

sergebulaev/linkedin-skills AI coding statistics: 73.3%

of 101 commits in February–September 15, 2026 were committed by an AI agent — a floor, not an estimate

73.3% agent · top contributor 68.9%13 contributors

team

A small group is using agents. Adoption has spread beyond one person but is not project-wide.

agent commits

other considered commits

agent contributors

68.9%

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

74assisted

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	74	73.3%

03Evidence

Inspect the matches

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

Matched commit samples

a472ef4c on GitHubv1.1.6: split out maintainer tooling, which --fresh proved was missingClaude Code
073effb8 on GitHubv1.1.5: a test system that answers "does this work"Claude Code
7c0cd59d on GitHubv1.1.4: check the Pixfaro key properly, and say where it goesClaude Code

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	119
Merge commits removed	−6
CI / dependency bots removed	−12
Considered	101

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 →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 sergebulaev/linkedin-skills

Scan another repository

Try

Month	Agent share	Considered commits
2026-04	75%	16
2026-05	71.4%	7
2026-06	50%	2
2026-07	100%	18
2026-08	20%	10
2026-09	75%	48