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self-review

Skill19 starsChanged 9 days agoMITView on GitHub

After drafting, reread the text as a native reader in its own language. If it still reads as machine-written, rewrite it. Works in any language. Sub-skill: load only when routed from the hook-everything entry skill, not for general writing or editing.

51 other projects use a version of this.

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Most recently taken up by

Used with

Projects with it also use latex-formatting, novelty-assessment and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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  • lingzhi227Skill

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  • +6 more from lingzhi227

The file

We split this skill into the rules it gives an agent

8 rules. 0 are common, 4 are distinctive, and 4 are very specific to this project.

  • 0

    Common

    Most of the 42 edited versions we read keep these.

  • 4

    Distinctive

    This author's own choices. Worth a look.

  • 4

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Run python3 tools/slop_scan.py <file> --fix-hints --hidden: when a shell is available.

    line 18
  2. Very specific:

    Repeat from step 2: Stop when the verdict is reads human and the score is <= 15/100, or after 3 rounds.

    line 20
  3. Very specific:

    Do not invent personal detail to sound human: No fake anecdotes, no made-up "last Tuesday" stories, no deliberate typos.

    line 28
  4. Distinctive:

    Run the checks for the language of the text.

    line 35
  5. Distinctive:

    Every sentence has about the same length and the same temperature.

    line 49
  6. Distinctive:

    Every point is hedged on both sides, and the text never takes a position.

    line 54
  7. Distinctive:

    Ask them in the text's own language, then answer with a quoted span.

    line 61
  8. Very specific:

    If I deleted the first and last sentences, would any fact be lost?

    line 67

“Common” is measured: kept by at least 6 in 10 of the 42 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Self-Review Loop (Read It Cold, Rewrite If It Still Smells)

A draft that passes a word list can still read as machine-written. This skill adds a reader's pass at the end: read the text as a skeptical native speaker, say whether it still reads as AI, and fix it until it doesn't. It works in any language.

Be honest about the limit. A model judging its own text is an unreliable detector, so this pass never relies on a feeling alone. Every verdict needs quoted evidence, and the scanner has the last word on score.


The Loop (maximum 3 rounds)

  1. Switch to the reader's language and register. Judge the text in the language it is written in. Never translate it to English to judge it, because translation hides the calques and register slips you are looking for. Picture one real reader: a native speaker of that language who reads a lot and distrusts polished copy.
  2. Read it cold, start to finish, without editing. Then give one verdict: reads human, unsure, or reads machine-made.
  3. Back the verdict with evidence. Quote the 3 spans that feel most machine-made and name the tell for each (uniform sentence weight, abstract noun as subject, see-saw concession, claim-example-moral paragraph, calque from English, no concrete anchor in 35 words). If you cannot quote a span, you have no verdict, so run the scan.
  4. Run python3 tools/slop_scan.py <file> --fix-hints --hidden when a shell is available. Treat a score above 15 or any hidden-character hit as a failed round, whatever the verdict was.
  5. Rewrite the flagged spans from scratch. Change the subject, the verb and the sentence shape. Swapping a synonym into the same skeleton fixes nothing (anti-slop Rule 72).
  6. Repeat from step 2. Stop when the verdict is reads human and the score is <= 15/100, or after 3 rounds. After round 3, list what still bothers you and hand it over instead of looping again.

What Never Changes in a Rewrite

  • Facts, numbers, names and dates stay exactly as they were. A rewrite that changes a figure is a new claim.
  • Quoted text stays word for word (anti-slop Rule 42).
  • Do not invent personal detail to sound human. No fake anecdotes, no made-up "last Tuesday" stories, no deliberate typos. value-check item 2 forbids fabricated receipts, and made-up texture counts. When a piece needs lived detail, leave a bracket for the person to fill: [your own example here].
  • Keep the author's register. A formal legal memo should come back formal and plain, not chatty.

Per-Language Reader Checks

Run the checks for the language of the text. For languages not listed, use the Universal block.

LanguageExtra tells a native reader notices
EnglishEm-dash glue, "not just X, it's Y", two-word rhetorical questions, three-adjective stacks, a closing summary paragraph.
VietnamesePronoun stuffing (bạn, của bạn, chúng tôi in every clause), việc + động từ nominalizations, không chỉ... mà còn... openers, stock phrases like trong bối cảnh.
Spanishen el mundo actual openers, juega un papel fundamental, calques of English passive voice, subject pronouns where Spanish drops them.
Frenchdans un monde en constante évolution, il est important de noter que, English-style noun stacks, vous and nous repeated where French drops them.
Germanin der heutigen schnelllebigen Welt, long nominal chains with -ung nouns, English word order in subordinate clauses.
Chinese / Japanese / KoreanStock frames (在当今..., 〜において重要な役割を果たします, 오늘날...), literal translation of English connectors, stiff register that no one speaks, over-explicit subjects in Japanese and Korean.
Universal (any language)See below.

Universal block, for any language

  • Every sentence has about the same length and the same temperature.
  • Paragraphs share one shape: claim, two examples, a moral.
  • Syntax follows English even though the words are not English (a calque of structure, not of vocabulary).
  • Register is flat and over-polite from the first line to the last, with no slang, no shorthand, no mid-thought correction.
  • Abstract nouns stand in for people and actions, and nothing in a 35-word stretch is concrete.
  • Every point is hedged on both sides, and the text never takes a position.
  • A list or heading structure imposed on something a person would have just said.

Quick Self-Test Questions

Ask them in the text's own language, then answer with a quoted span.

  1. Which sentence would a native speaker never say out loud to a colleague?
  2. Where does the text explain something nobody asked about?
  3. Which paragraph could be moved to a different article without anyone noticing?
  4. Where does the writer sound more careful than a person would be?
  5. If I deleted the first and last sentences, would any fact be lost? (anti-slop Rule 73)

Hand-Off

End the loop with one line for the user: the final verdict, the scanner score if it ran, and anything left unresolved. Then run skills/value-check.

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