Writing
Plugin
humanizer-academic
A skill that removes signs of AI-generated writing from academic medical papers, making them sound more natural and professionally written.
Plugin Signal61/100Solid
maintained97
capable14
documented75
adopted52
Install
$ npx -y skills add matsuikentaro1/humanizer_academic --agent claude-code
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Maintenance
Python
Language
9d ago
Last commit
8mo ago
Created
2h ago
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What's inside
README
Humanizer Academic
A skill that removes signs of AI-generated writing from academic medical papers, making them sound more natural and professionally written.
The main instructions are in SKILL.md, with reusable examples in references/reader-clarity.md. Both are plain text, so you do not need Claude Code to use them. scripts/humanizer_check.py is an optional checker for agents that can run commands; the skill works without it.
Usage
In a browser (Claude, ChatGPT, or anything that takes an attachment)
- Download
SKILL.mdandreferences/reader-clarity.mdfrom this repository. - Upload both files to the chat along with the text you want to edit.
- Ask:
Apply this skill to the following manuscript text: [your text]
That is all. No installation.
You do not need the checker script in a browser chat; the skill does the same checks by hand. If your chat can run code, you can also upload scripts/humanizer_check.py, and the skill will run it on its draft.
In Claude Code
Clone into your skills directory:
mkdir -p ~/.claude/skills
git clone https://github.com/matsuikentaro1/humanizer_academic.git ~/.claude/skills/humanizer_academic
Or, from a downloaded copy of the repository:
mkdir -p ~/.claude/skills/humanizer_academic/references ~/.claude/skills/humanizer_academic/scripts
cp SKILL.md ~/.claude/skills/humanizer_academic/
cp references/reader-clarity.md ~/.claude/skills/humanizer_academic/references/
cp scripts/humanizer_check.py ~/.claude/skills/humanizer_academic/scripts/
Optional checker
Language models miscount words and tend to grade their own drafts generously. When Python is available, the skill runs scripts/humanizer_check.py once on its draft before the final checks. The script uses only the standard library and reports:
- the number of words in each sentence, paragraph by paragraph, and the paragraphs that fail the Pattern 34 rhythm criterion
- em dashes and curly quotes
- three consecutive sentences with the same first word, and "Additionally" used more than once in a paragraph
- numbers that appear in the revision but not in the original
- words named in the patterns, listed as candidates to read in context
It gives no score, and a candidate word is not a violation. If Python is missing, the skill does the same checks by hand. You can also run it yourself:
python scripts/humanizer_check.py revised.txt --original original.txt
The skill loads itself when it is relevant, so you can simply ask:
Please humanize this academic text: [your text]
Overview
Based on Wikipedia's "Signs of AI writing" guide, adapted for medical and scientific literature. Examples are derived from the EMPA-REG OUTCOME trial publications and from the author's (K. Matsui) observations during academic manuscript editing.
Key Insight from Wikipedia
"LLMs use statistical algorithms to guess what should come next. The result tends toward the most statistically likely result that applies to the widest variety of cases."
34 Patterns Detected (with Before/After Examples)
Content Patterns
| # | Pattern | Before | After |
|---|---|---|---|
| 1 | Significance inflation | "represents a pivotal challenge in the evolving landscape" | "is highly prevalent in patients with diabetes" |
| 2 | Notability claims | "landmark trial, led by renowned investigators" | "A total of 7020 patients..." |
| 3 | Superficial -ing analyses | "highlighting the cardioprotective effects" | Report data without interpretation |
| 4 | Promotional language | "groundbreaking study showcases the profound impact" | "empagliflozin reduced heart failure hospitalization" |
| 5 | Vague attributions | "Studies have shown... Experts argue..." | "In the EMPA-REG OUTCOME trial..." |
| 6 | Formulaic challenges | "Despite challenges... future outlook" | State specific limitations |
Language Patterns
| # | Pattern | Before | After |
|---|---|---|---|
| 7 | AI vocabulary | "pivotal... landscape... crucial" | Remove or replace with simple words (note: "Additionally" is allowed once per paragraph) |
| 8 | Copula avoidance | "serves as... standing as... representing" | "is" |
| 9 | Negative parallelisms | "Not only X but also Y" | "X and Y" |
| 10 | Rule of three | "efficacy, safety, and tolerability" | Use natural number of items |
| 11 | Synonym cycling & term consistency | "Patients... Participants... Subjects" | "Patients" throughout (same construct = same term) |
| 12 | False ranges | "from renal function to cardiac outcomes" | List benefits directly |
Style Patterns
| # | Pattern | Before | After |
|---|---|---|---|
| 13 | Em dash elimination | "benefits—a 35% reduction—appeared early—" | Use commas, parentheses, or periods. Every em dash is replaced, including natural-looking ones |
| 14 | Title Case Headings | "Statistical Analysis And Primary Endpoints" | "Statistical analysis and primary endpoints" |
| 15 | Curly quotes | “clinically significant” | "clinically significant" |
Filler and Hedging
| # | Pattern | Before | After |
|---|---|---|---|
| 16 | Filler phrases | "In order to", "Due to the fact that" | "To", "Because" |
| 17 | Redundant multi-layered hedging | "may suggest... have the potential to confer" | "suggest... may reduce" (keep 1-2 hedges) |
| 18 | Generic conclusions | "The future looks bright" | Specific findings and implications |
LLM-Specific Word Choice Patterns (v1.1.0)
| # | Pattern | Before | After |
|---|---|---|---|
| 19 | "linked to" → "associated with" (context-dependent) | "has been linked to shorter sleep duration" | "has been reported to be associated with" |
| 20 | "Beyond" → "In addition to" | "Beyond the association with..." | "In addition to the association with..." |
| 21 | "via" → "through" | "obtained via the online form" | "obtained through an online form" |
| 22 | Insufficient hedging | "may reduce the risk of..." | "may help reduce the risk of..." |
| 23 | Artificially condensed expressions | "fatigue–sleepiness cycle", "mutual reinforcement" | "cycle of fatigue and sleepiness", "a self-reinforcing cycle, with each behavior possibly exacerbating the other" |
| 24 | "where" as a non-locative connector | "...at the most intensive level, where almost daily use was..." | "...at the most intensive level, with almost daily use..." |
| 25 | "yield" as a result verb | "did not yield stable estimates" | "failed to produce stable estimates" |
| 26 | Minor word-choice refinements | "interpretations remain speculative", "speculative given the small sizes" | "interpretations are still speculative", "speculative due to the small sizes" |
Cohesion and Connective Patterns (v1.1.4–1.3.0)
| # | Pattern | Before | After |
|---|---|---|---|
| 27 | Preserve logical discourse markers + vary by relation (do NOT over-trim) | (aggressive removal of "Although / Whereas / Thus / Based on these results") | Keep connectives that make the logic explicit; vary them by relation (result / contrast / concession) only to avoid mechanical repetition, never for decoration |
| 28 | Re-contextualize over-condensed semantic links | "unmet needs to discuss their difficulties" | "unmet needs when it comes to discussing their difficulties" |
| 29 | Ornamental -ly intensifier adverbs | "markedly reduced", "critically important", "remarkably consistent" | Remove decorative intensifiers; keep functional ones ("slightly", "consistently", "approximately") |
| 30 | Connective-preserving edits (never bare-delete a transition) | "X reduced death. The benefit appeared within months." (choppy) | "X also reduced death, and this benefit appeared within months." |
| 31 | Paragraph cohesion (old-to-new flow + paragraph-opening markers) | Disconnected sentences after editing | Mandatory final check: each sentence links to the previous one; contrast/continuity openers (However / On the other hand / Overall / Taken together) survive |
| 32 | Paraphrastic repetition | "X is associated with Y. In other words, X may contribute to Y. That is, X plays a role in Y." | State each claim once; keep the most specific version |
| 33 | Content-free evaluation sentences | "This is a noteworthy finding." "This observation is of clinical significance." | Delete standalone verdicts; if important, show why with data or mechanism |
Sentence Rhythm and Reader Clarity (v2.3)
| # | Pattern | Before | After |
|---|---|---|---|
| 34 | Sentence rhythm & burstiness, in the service of clarity | Uniform 18-22 word sentences; stacked conditions and unclear comparisons | Vary sentence lengths and openings in every paragraph by splitting stacked sentences and combining related supporting sentences; keep short claim sentences short |
Reader clarity comes first. Preserve actors, comparisons, conditions, and logical relationships. Shorten by removing low-priority or repetitive sentences rather than compressing essential meaning. Burstiness is still required in every paragraph (mandatory rhythm check), but it is obtained only through edits that keep meaning explicit, and never by merging the author's short claim sentences. See the eight diagnostic examples.
Preserved Academic Writing (do NOT flag as AI)
The skill explicitly preserves standard academic writing that was previously over-corrected:
- Transitional phrases: "Notably,", "Furthermore,", "In contrast,", etc.
- Logical discourse markers: "Although", "Whereas", "Thus", "Based on these results", "As expected", etc. (Pattern 27)
- Functional -ly adverbs: "slightly", "consistently", "modestly", "approximately" (Pattern 29)
- Interrogative sentence openers: "Who selects into...", "What predicts...", etc.
- "Additionally" up to once per paragraph (Pattern 7 exception)
- Attribution phrases with citations: "Prior studies have shown that...", "Evidence suggests that...", etc.
These are only flagged when used in excessive clusters or without supporting citations/data.
Full Example
Before (AI-sounding):
Heart failure represents a pivotal challenge in the evolving landscape of diabetes care, underscoring the critical importance of addressing cardiovascular comorbidities. This groundbreaking study showcases the profound impact of empagliflozin. Additionally, empagliflozin reduced the risk of hospitalization for heart failure or cardiovascular death by 34%—a remarkable finding—highlighting the cardioprotective effects of this intervention. The future looks bright for patients with type 2 diabetes.
After (Humanized):
Heart failure is highly prevalent in patients with diabetes, occurring in more than one in five patients with type 2 diabetes aged over 65 years. In the EMPA-REG OUTCOME trial, empagliflozin reduced the risk of hospitalization for heart failure or cardiovascular death by 34%. The benefit was consistent in patients with and without heart failure at baseline.
References
- Wikipedia: Signs of AI writing - Primary source for AI writing patterns
- WikiProject AI Cleanup - Maintaining organization
Examples Source
Medical paper examples (Patterns 1–18) are adapted from:
Fitchett D, Inzucchi SE, Cannon CP, et al. Empagliflozin Reduced Mortality and Hospitalization for Heart Failure Across the Spectrum of Cardiovascular Risk in the EMPA-REG OUTCOME Trial. Circulation. 2019;139(11):1384-1395. doi:10.1161/CIRCULATIONAHA.118.037778
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FAQ
humanizer-academic is a Claude Code plugin with 1 hand-picked skill, indexed on Flowy in the Writing category. Install it with the command on its page. It includes humanizer_academic. Its skills do not fire on their own yet. Request auto-invocation to have Flowy route them as you prompt. Free and open source.
- What is humanizer-academic?
- A skill that removes signs of AI-generated writing from academic medical papers, making them sound more natural and professionally written. The main instructions are in SKILL.md, with reusable examples in references/reader-clarity.md.
- How do I install humanizer-academic?
- Run these in Claude Code: npx -y skills add matsuikentaro1/humanizer_academic --agent claude-code. Then prompt normally.
- Does humanizer-academic auto-invoke its skills?
- Not yet. It is indexed on Flowy as a plain plugin. Request auto-invocation on its page and Flowy will route its skills for you as you prompt.
- Is humanizer-academic free?
- Yes. Flowy is free and open source, with nothing gated. You can read every skill in full before you install.
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