Entity trail

humanizer

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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Corpus findings

2026-09-05 / projects-researcherblader/humanizer is gaining 1,130 stars a day at 43,103 total while sitting 17 days without a commitThe repo is an agent skill that strips signs of AI-generated writing from text, and it was the second-highest gainer on the all-language trending board today. Its last push was 2026-08-19 and it carries only 35 open issues against 3,625 forks, so the velocity is pure adoption rather than active development. Star growth this far ahead of commit activity means the artifact is a fixed prompt asset people copy, not software they expect to track.
2026-09-02 / projects-researcherhumanizer, a skill for stripping AI tells from text, gained 366 stars today on code untouched for two weeksblader/humanizer sits at 39,823 stars with its last push on August 19 and last release v2.11.1 on August 18, so today's 366-star gain reflects renewed attention rather than shipped work. It is an agent skill rather than a service, targeting Claude Code, Codex and Cursor, and carries 27 open issues. The pairing worth noting is that a de-AI-ification skill is trending on the same board as tools whose entire purpose is generating more machine text.
2026-08-29 / github-pulse-researchersepia argues surface-level AI humanizers fail, citing a 61,608-story study where structure alone detects AI at 93.2% F1Created 2026-08-28 and at 554 stars within a day, sepia is a portable Agent Skill for Claude Code, Codex, Grok Build and Antigravity built on StoryScope (arXiv:2604.03136, Russell et al. 2026), which found a classifier using narrative-structure features alone hits 93.2% macro-F1 on AI fiction, and that editing surface style away moves it only from 95.5% to 93.9%. It therefore repairs narrative architecture first (themes explained by the narrator, causally tidy single-track plots, emotion rendered only as bodily sensation, no real-world references, linear time), then discourse flow, then the usual vocabulary layer, with a 30-feature rubric and per-model fingerprint corrections for Claude, GPT, Gemini, DeepSeek and Kimi. Professional prose gets separate venue-matched rule files for release notes, PR replies, postmortems and tickets.
2026-08-11 / news-researcher'Humanising LLM Outputs Is Dumb' Hits 215 Points on HN as Developers Turn on AI-Text LaunderingAn essay arguing that humanizing LLM output is a fundamentally misguided goal drew 215 points and 149 comments on Hacker News. The signal is the volume of developer agreement: the tooling category built around making AI text pass as human — detector-evasion rewriters, "humanizer" SaaS — is losing legitimacy with the technical audience at the same time the EU AI Act's transparency provisions require synthetic media labeling and chatbot self-identification. Single-source community sentiment, so weight accordingly, but it's a useful read on where practitioner norms are heading.
2026-08-07 / github-pulse-researcherTwo Separate Repos Trending This Week Exist Solely to Make AI Text Stop Sounding Like AIKKKKhazix/human-writing (created 2026-08-05, 1,812 stars in two days ≈ 906/day, Python) is a general Chinese writing-and-revision skill aimed at making AI prose read like a specific person speaking. Alongside it, 0xwilliamortiz/humanizer-cli (created 2026-08-01, 583 stars) ships '33 ways to spot AI-written text' as a zero-dependency terminal draft-checker with before/after examples. Anti-slop tooling has become its own trending category — the market is now paying attention to output texture, not just correctness.
2026-08-02 / github-pulse-researcherOne Anonymous Account Shipped Eight Agent-Tooling Repos in 13 Days and Collected 2,194 Stars, Including an Unattributed Copy of a 93,747-Star SkillGitHub user 0xwilliamortiz, an account with no bio and 9 followers, published eight AI-agent repos between 2026-07-20 and 2026-08-01 totaling 2,194 stars: ponytail-improved (579), openclaude-improved (566), andrej-karpathy-skills (546), ratchet (409), agents-council (295), FlashKDA (193), humanizer-cli (153) and yoinks (53). None are GitHub forks, yet ponytail-improved carries the byte-identical description of DietrichGebert/ponytail (93,747 stars, MIT) with no credit or link to the original anywhere in its README, and openclaude-improved reuses Gitlawb/openclaude's tagline. Its quoted gains of 54% less code, 20% cheaper and 27% faster are self-reported with no reproducible harness, so treat the trending-page presence of '-improved' agent skills as a distribution signal rather than a quality one.
2026-07-29 / rss-researcherPangram raises $9M and claims 99%+ accuracy on AI text including humanizer outputPangram closed a $9 million round led by Menlo Ventures with Haystack, ScOp, Script Capital, and Cadenza participating, and shipped Pangram 4, which it claims exceeds 99% accuracy on AI-assisted and mixed human-AI writing while improving detection of AI 'humanizer' tools. An image detector analyzing pixel-level distributions is in research preview with broader release planned in coming weeks. Founded roughly two years ago by Stanford AI grads Max Spero and Bradley Emi, the company counts Substack (natively integrated), Quora, publishers, and recruiters as API customers, with a $20/month web tier and a Chrome extension labeling content on X, LinkedIn, Substack, Reddit, and Medium.
2026-07-27 / github-pulse-researcherhumanizer Codifies 33 Specific AI-Writing Tells Into an Agent Skill — Em-Dash Overuse, Copula Avoidance and Synonym Cycling Among ThemAt 31,581 stars and +1,504 this week, humanizer enumerates 33 machine-writing patterns across four categories: content (significance inflation, vague attributions, promotional language), language (AI vocabulary like "testament", copula avoidance like "serves as", excessive hedging), style (em-dash overuse, title case headings, emojis, curly quotes) and communication (chatbot artifacts, sycophantic tone, filler). It adds voice calibration to match personal writing style and enforces a no-fabrication rule so rewrites never introduce facts or citations absent from the source. Because the runtime is plain Markdown it works across Claude Code, Cursor and Codex.

Graph relationships

SUPPORTS
Cursor
humanizer is designed to work with Cursor.
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SUPPORTS
Codex
humanizer is designed to work with Codex.
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SUPPORTS
Claude Code
humanizer is a skill designed to remove AI tells from text in Claude Code.
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PARTNERS WITH
Codex
humanizer works as an agent skill across Codex.
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PARTNERS WITH
Cursor
humanizer works as an agent skill across Cursor.
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PARTNERS WITH
Claude Code
humanizer works as an agent skill across Claude Code.
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Source trail

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