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blader
humanizer
Python2026–2026
blader / humanizer

humanizer

Agent skill that removes signs of AI-generated writing from text

16Distinct people
26Mentions
1Explicit recommenders
68.5KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Agent skill that removes signs of AI-generated writing from text

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

Tbh, I did spend a lot of time trying to ground it and de-slopify it - verified nothing was halucinated and went through 10 iterations to get to this. It's almost like…

asenna used a recommendation phrase. One indexed comment matches. This is a phrase match, not a verdict.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 10:02:05 AM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month26 dated mentions

Observed mentions: 2026-01-19 14:21:59 UTC to 2026-10-27 15:48:11 UTC.

02462026-01-01 00:00:00 UTC to 2026-02-01 00:00:00 UTC (exclusive): 4 mentions; 2 submissions, 2 commentsJan 20262026-02-01 00:00:00 UTC to 2026-03-01 00:00:00 UTC (exclusive): 3 mentions; 1 submissions, 2 comments2026-03-01 00:00:00 UTC to 2026-04-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2026-04-01 00:00:00 UTC to 2026-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-05-01 00:00:00 UTC to 2026-06-01 00:00:00 UTC (exclusive): 4 mentions; 0 submissions, 4 commentsMay 20262026-06-01 00:00:00 UTC to 2026-07-01 00:00:00 UTC (exclusive): 6 mentions; 0 submissions, 6 comments2026-07-01 00:00:00 UTC to 2026-08-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments2026-08-01 00:00:00 UTC to 2026-09-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-09-01 00:00:00 UTC to 2026-10-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2026-10-01 00:00:00 UTC to 2026-11-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 commentsOct 2026

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Jan 20262026-01-01 00:00:00 UTC2026-02-01 00:00:00 UTC422
Feb 20262026-02-01 00:00:00 UTC2026-03-01 00:00:00 UTC312
Mar 20262026-03-01 00:00:00 UTC2026-04-01 00:00:00 UTC110
Apr 20262026-04-01 00:00:00 UTC2026-05-01 00:00:00 UTC000
May 20262026-05-01 00:00:00 UTC2026-06-01 00:00:00 UTC404
Jun 20262026-06-01 00:00:00 UTC2026-07-01 00:00:00 UTC606
Jul 20262026-07-01 00:00:00 UTC2026-08-01 00:00:00 UTC303
Aug 20262026-08-01 00:00:00 UTC2026-09-01 00:00:00 UTC101
Sep 20262026-09-01 00:00:00 UTC2026-10-01 00:00:00 UTC202
Oct 20262026-10-01 00:00:00 UTC2026-11-01 00:00:00 UTC211

What Hacker News says

6 sources
I'm going to do a simonw here and coin "Markdown hoarding" for the Claudeism of producing reams of hyper-dense prose and compounding it with every commit that touches docs. The documentation gets more and more bloated. The default Claude voice is breathless, jargon-heavy showboating: WebRTC transport (trickle ICE) — RTCPeerConnection data channels with trickle signaling; same-machine mDNS-loopback rewrite. Browser/device-verified. peerd-distributed/transport/transports/webrtc.js TOFU rootfs integrity pin — pure decision logic: trust-on-first-use pin of base-image size + first-64KiB SHA-256, verified each boot, fails closed on drift. Head-only by construction — a faithful-head/tampered-tail host is an acknowledged residual gap. peerd-engine/image-pin.js (partial) PDF reading (read_pdf) — pdf.js text-layer extraction with opt-
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in SRI-pinned OCR engine + page assembly. pdf/, tools/defs/read-pdf.js This isn't a critique of the author, more of Opus, but I'd be curious what effect https://github.com/blader/humanizer/blob/main/SKILL.md might have.
In Show HN: peerd – AI agent harness that runs entirely in your browser
I use PI ( https://pi.dev ) and ( https://hermes-agent.nousresearch.com/ ) as the main drivers together with deepseek-v4-pro as the main model (~10M/day tokens overall there). Hermes basically rules my personal life at this point - it is a _very_ useful personal assistant. I also use it at work (integrated at Slack) and at this point it answers most of both my emails and slack messages (I calibrated https://github.com/blader/humanizer with a large corpus of my own voice to make it less annoying for the others). My routine now involving walking in circles while exchanging messages with hermes directing it how to answer this or that... Hermes uses an llm-wiki ( https://gist.github.com/karpathy/442a6bf555914893e9891c11519... ) as a source of information when drafting suggested replies - I have a cronjob that feeds it all emails, slack messag
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es, meeting minutes every single day. Claude Code with Opus 4.6 for multimodal/vision, design and writing tasks ("Create a crisp memo from this meeting transcription" is a prompt that will bring great results with either Opus 4.6 or GLM-5.1) - very recently I started to use https://github.com/anomalyco/opencode occasionally with opus models too (I am forcing myself a little bit because it is hard to help people with a tool you are unfamiliar with). For building software automatically I currently use one of the harness above for for launching https://tamandua-tetradactyla.nfshost.com/ feature-dev-merge-worktree runs (it provides workflows on top of PI+deepseek). Where it comes from: until recently I used https://steve-yegge.medium.com/welcome-to-gas-town-4f25ee16d... for automatic software building but while planning an AI bootcamp I concluded that teaching Gas Town along with everything else would be impossible (too hard/complex), and decided to teach https://github.com/snarktank/antfarm instead but did not want to add OpenClaw as one more dependency - so I built Tamandua ( https://github.com/igorhvr/tamandua ) and I ended up using it all the time! I now every single day before going to sleep launch a couple of runs and it is very cool waking up to see them done. For autoresearch-like, optimization, and other tasks with a very clear measurable goal (such as increasing test coverage, changing things from one programming language to another, etc) I use https://github.com/davebcn87/pi-autoresearch (100% of the time on top of deepseek-v4-pro). For debugging or very hard problems I use codex w/ GPT5.5. I don´t like its personality (lazy) but I do think it is smartest model available. As evidence, here is a commit of a problem where I tried Opus 4.8, Deepseek-v4-pro and a couple of other models and they all failed to understand what the bug was: https://github.com/NousResearch/hermes-agent/pull/38198/chan... - once the bug was found within codex I launched from it a tamandua bug-fix-merge-worktree run on top of deepseek-v4-pro that created the commit itself... As a web application I use OpenWebUI and I am specially fond of the notes feature ( https://docs.openwebui.com/features/notes/ ) which I did not find anywhere else. Last but not least, I love playing with local models. https://huggingface.co/Qwen/Qwen3-Coder-480B-A35B-Instruct is my current favorite for coding and deepseek-r1 for general tasks. I also started yesterday testing https://github.com/antirez/ds4 - it works _very_ well from what I could see so far. What comes next? Trying to figure out what is the "deepseek-v4-pro of multimodal" model (frontier performance, efficient/comparatively cheap to run, support for image/audio/video/etc). Currently using kimi-k2.6, will test Minimax M3 soon. Ah, almost forgot: https://huggingface.co/microsoft/VibeVoice-ASR will give you AMAZINGLY good meeting transcriptions (my hermes vibecoded a program to use it). Seriously, night and day difference from what the big players provide natively in their platforms. Have 8 people talking in 3 different languages? No problem - you will need a bit of patience and beefy hardware, only..
In Ask HN: What is your (AI) dev tech stack / workflow?

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