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.

Countly is a privacy-first, AI-powered analytics and engagement platform for understanding and optimizing customer journeys across digital applications, from desktop and mobile to IoT and connected environments.

01Result

Countly/countly-server ↗

Countly/countly-server AI coding statistics: 54%

of 644 commits in February–September 15, 2026 were committed by an AI agent — a floor, not an estimate

54% agent · top contributor 45.1%13 contributors

org-wide

Adoption is broad. Many contributors are committing agent-authored work, which is what a real organisational rollout looks like.

348

agent commits

296

other considered commits

agent contributors

45.1%

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

347assisted

1autonomous

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: 87.5%. Bars are scaled to that peak, not to 100%.

Which agents

Agent	Vendor	Commits	Share
Claude Code	Anthropic	337	52.3%
GitHub Copilot	GitHub	11	1.7%

03Evidence

Inspect the matches

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

Matched commit samples

c8d9e16f on GitHubchore(test): make the e2e suite Cypress 16 compatibleClaude Code
74587b4c on GitHubbuild(deps): pin qs to 6.16.0 through an npm overrideClaude Code
a0d255bf on GitHubchore: sync merge shepherd — auto-merge-priority labelClaude Code
f69ff4d4 on GitHubPotential fix for pull request findingGitHub Copilot
b3ad2973 on GitHubApply suggestions from code reviewGitHub Copilot
3ce9a7ed on GitHubApply suggestions from code reviewGitHub 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	1,692
Merge commits removed	−831
CI / dependency bots removed	−217
Considered	644

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 →JavaScript AI coding statisticsCompare evidence across JavaScript 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 Countly/countly-server

Scan another repository

Try

Month	Agent share	Considered commits
2026-02	0%	46
2026-03	0%	81
2026-04	0%	34
2026-05	63.5%	63
2026-06	85.2%	196
2026-07	81.3%	75
2026-08	49.6%	133
2026-09	87.5%	16