Nicheloom

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Slop Meter for GitHub

Details

External ID
47223316
Source
HN
Company
—
Product
—
Website domain
—
Launched
March 2, 2026
Cohort
—
Upvotes
6
Upvotes percentile
0.2853628536285363
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

About 6 years ago I wrote a blog post [0] with some ideas on how to help popular open source maintainers deal with all the noise on Github. Patted myself in the back and never did anything about it :)There's recently been a lot more discussion around this due to AI, so I've built a simple tool called "Slop Meter" [1]. It gives maintainers a quick snapshot of the user's history in open source:1) Do they just open issues and expect you to do everything, or will they put in the work to fix the problems and open a PR? What's the issues : PR ratio? 2) If they do contribute, what percentage of their PRs actually gets merged?I feel like these are the two most important signals when triaging what to pay attention to in open source.You can install this on any Github repo and it will automatically post a comment with the stats. We do not run this on maintainers or existing contributors.You can also go on the web and look up a Github profile; it will take a minute or so to import depending on how much public data they have (maybe longer if this makes the front page...).Example profile: https://slopmeter.kernellabs.ai/u/mitchellhIf you are an OSS maintainer, I'd love to hear any feedback.[0] https://www.alessiofanelli.com/posts/how-can-we-help-oss-mai... [1] https://slopmeter.kernellabs.ai/

Enrichment

Theme
git and repository workflow tools
Vertical
Horizontal
Function
Dev tools
Audience
Developer
AI stance
AI feature
Project type
Hobby / open-source project
Normalized one-liner
detect low-quality ai-generated code on github
Manually corrected
False

Could you build this?

Yes A GitHub spam detection tool that fetches issues/PRs via the GitHub API and uses heuristics or LLM evaluation to flag low-quality slop is simple to build with an AI assistant.

Discussion

No comments on this launch.

Competitors

Other products that read as similar to this one — 77 launches clear the similarity bar, closest 8 shown.

Attention rank: #56 of 78 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 123 days after the earliest competitor.

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