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New system rates AI code contribution and human oversight in open source

Greg Kamradt has developed "AI Code Rating" (ACR), a system to indicate project maintenance and AI code contribution. The rating uses three characters to denote the maintainer's expertise, the percentage of AI-written code, and the extent of human review for AI-generated code. This information is intended to be placed in an ACR.md file within a project repository. AI

IMPACT Provides a standardized way for open-source projects to disclose AI code contribution and human oversight.

RANK_REASON The item describes a new tool or system for rating code, not a frontier release, significant industry move, or research paper.

Read on Mastodon — mastodon.social →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New system rates AI code contribution and human oversight in open source

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11 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
The item describes a new tool or system for rating code, not a frontier release, significant industry move, or research paper.
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Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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product, other
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AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
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Breaking (< 6h)
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Full methodology in our editorial standards.

COVERAGE [1]

  1. Mastodon — mastodon.social TIER_1 English(EN) · gregdotca ·

    I made AI Code Rating. It's three characters that tell you who maintains a project, how much of its code AI wrote, and how closely a person checked it. A2b = ex

    I made AI Code Rating. It's three characters that tell you who maintains a project, how much of its code AI wrote, and how closely a person checked it. A2b = expert maintainer, 26–50% AI-written, every AI change reviewed. B0a = experienced maintainer, no AI code. It goes in an AC…