44 added, 171 removed. Audit A to A.
---
name: anti-slop-writing
- description: Make writing sound like a person wrote it. Rewrites drafts that read as machine-generated, restores voice that AI editing flattened, and audits text for AI tells when asked. Use when a draft feels generic or corporate, when asked to de-slop or humanize text, when polishing anything an LLM helped write, before publishing a post or doc, or when someone asks whether writing "sounds like AI". Do not use it to adjudicate authorship disputes: this skill names patterns and never outputs an AI-vs-human verdict.
+ description: Make writing sound like a person wrote it. Rewrites drafts that read as machine-generated, restores voice that AI editing flattened, and audits text for AI tells when asked. Use when a draft feels generic or corporate, when polishing anything an LLM helped write, before publishing a post or doc, or when someone asks whether writing "sounds like AI".
---
# Anti-Slop Writing
Make the writing better and make it sound like a person. Removing tells is the means, not the end.
Distilled from 45 published anti-slop and humanizing skills. Harvest method and hard counts in
`references/corpus-evidence.md`.
- **Prefer clean drafting to cleanup.** When you are also the author, apply these rules while
- writing rather than running a repair pass afterwards. A post-hoc pass recovers less than not
- generating the tells in the first place; this skill exists for text that already exists.
-
## Read this first, or the rest will mislead you
**Word lists are the weakest signal and they are going stale.** `delve`, `tapestry`, `vibrant`,
and `myriad` are largely absent from current frontier-model output. A draft that avoids them is
not human. It is just newer.
Four consequences that govern everything below:
1. **Structure outlives vocabulary.** Sentence-shape and paragraph-shape tells survive model
updates. Word tells do not. Weight structure higher.
2. **Tells are diagnostic in clusters, not alone.** One em dash means nothing. Em dashes plus a
rule-of-three plus an "In conclusion" section plus uniform paragraph lengths is a confession.
Never flag a single occurrence as evidence.
- 3. **The failure mode is over-correction.** Stripping every flagged token turns distinctive
- human writing into flat, cautious prose. That is a different kind of slop, and it is the one
- this skill is most likely to cause. Deleting is easy; the hard half is Step 6.
+ 3. **The failure mode is over-correction (The Twin Ditches).**
+ - *Ditch A (Academic Whitepaper Slop):* Stripping personality pushes the draft into a detached,
+ passive, 3rd-person clinical whitepaper or royal "we" that reads like a committee report.
+ - *Ditch B (Performed Incompetence):* Confusing human voice with self-deprecation, confusion,
+ or beginner apologies. If the author is a senior engineer who builds production systems,
+ do NOT strip their authority or force faux-modesty.
4. **These heuristics are biased against non-native English speakers.** Simpler vocabulary,
more formal connectives, and more even sentence rhythm are all normal in competent
second-language writing, and all trip the checks below. Never tell someone their writing
"sounds like AI" on rhythm and connective evidence alone. Name specific patterns and let
them judge.
## Three modes
**IMPROVE (default).** The draft needs to be better and sound like a person. Rewrite it. Return
the edited draft plus a `What changed` section. This is what to do unless told otherwise.
**AUDIT.** Someone wants to know if a piece reads as machine-written, without a rewrite. Name
each pattern, quote the line, give the fix in a few words. Do not rewrite. Do not output a
probability that the text was AI-generated: you cannot know that, detectors guess, and they are
most wrong against the writers named in point 4. Named patterns are checkable. A score is not.
- Cluster bands calibrate your recommendation in this mode; they never authorize an edit.
- A follow-up pass after an audit starts over at Step 0 with a fresh baseline and dose decision;
- do not carry state across modes.
-
**RESTORE.** A specific and common case: the draft was *already* edited by an AI and came back
- flattened. The tells are mostly gone but so is the person. Work from whatever earlier draft or
- sample of the author's writing you can get.
-
- RESTORE runs Steps 0, 6, and 7. During Step 0, check what the polish pass left behind: any Tier
- 1 word, banned phrase, paste-tell, or failing mechanical check gets its minimal fix from the
- relevant step first. Paste-tells are stripped in every mode without a judgment call. Dose here
- describes how far Step 6 reaches: light restores flagged losses only; medium also rebuilds
- rhythm and specificity from what the author had.
-
- If no earlier draft or writing sample exists at all, do not invent a personality. Mine the
- current draft for its core point and any opinion it contains, restore those, and cap the pass
- at medium. On this path skip the eight-trait diff walk in Step 6, because nothing was
- subtracted; instead check every restored addition against the mined core point.
+ flattened. The tells are gone but so is the person. Skip Steps 3 and 4, go straight to Step 6,
+ and work from whatever earlier draft or sample of the author's writing you can get.
## Dose
Decide before editing. State which you chose in the output.
| Dose | When | What you touch |
|---|---|---|
| **Light** | strong draft, a few tells | named patterns only, nothing else |
| **Medium** | default | patterns, rhythm, and specificity |
| **Heavy** | reads as fully generated, author agrees | structure and argument order too |
- **Heavy is opt-in.** Never restructure someone's argument because it would be tidier. Ask the
- author before running heavy. If the draft needs a heavy pass and you were not asked for one, do
- a medium pass and say what a heavy one would change as a `Heavy plan` bullet under
- `Left alone deliberately`.
-
- If the author authorizes heavy after editing began, finish the current dose first, then run
- heavy as a second pass on the edited draft. State both doses in `What changed`:
- `Dose: medium, then heavy on request`. Never restart from the original draft; re-running
- subtraction over already-cut text manufactures the over-correction this skill fears.
+ **Heavy is opt-in.** Never restructure someone's argument because it would be tidier. If the
+ draft needs a heavy pass and you were not asked for one, do a medium pass and say what a heavy
+ one would change.
If the draft is already good, **say so and stop.** "Two minor things, otherwise this reads fine"
is a complete and correct output. Manufacturing findings to look useful is its own failure.
## Genre calibration
The rules below are not uniform across formats. Set this in Step 0.
| Format | Em dashes | Contractions | Fragments | Structure |
|---|---|---|---|---|
- | Social post | zero under 500w | yes | yes | loose |
- | Outreach, cold email | zero | yes | yes | no headings, one ask |
+ | Social post | zero | yes | yes | loose |
| Blog, essay | ≤1 per 500w | yes | sparingly | headings ok |
- | Launch post, release notes | ≤1 per 500w | yes | sparingly | callouts and taglines allowed; comparative claims still need numbers |
| Technical docs | ≤1 per 500w | yes | no | headings required |
- | Resume, cover letter | zero | sparingly | verb-first fragments ok | no admissions injected; skip the Step 6 additions |
- | Slide deck | zero | no | deck-native | bold and list conventions are the medium; formatting-tells layout bans do not apply |
| Commit message | zero | no | no | imperative subject, prose body |
| Legal, medical, formal | as house style | no | no | house style wins |
- Precedence, highest first: **house style guide > supplied writing sample > genre table >
- this skill's defaults.** A sample overrides every threshold in `references/detection-rubric.md`
- except the hard rules; where a genre row conflicts with the Step 6 keep-lists (commit messages
- and legal text take no contractions), the genre table wins. Mixed-format pieces take the
- stricter dash cell and the looser structure cell.
-
- ## Out of scope, and what to say instead
-
- - "Make this shorter." Length is not slop. Agree a target length and cut by argument, or
- decline; this skill's rules can lengthen a draft when specificity demands it.
- - "Make it punchier for social." Hooks and kickers are the genre there. Apply the social-post
- row rather than the fake-profound-kicker ban.
- - "Rewrite it in [named person]'s voice." Requires their writing samples. Without samples,
- decline rather than performing Generic Executive Tone.
- - Slide decks and UI copy follow their genre rows above, not the blog defaults.
+ Where a house style guide exists, it beats this skill.
## Procedure
### 0. Establish the baseline
- Step 0 runs in every mode, without exception; RESTORE sources its voice signals from the
- earlier draft or sample instead of the current one.
-
Read the whole draft. Note internally, do not output:
- The core point in one sentence. If you cannot find it, ask rather than guessing.
- 3 to 5 **voice signals to protect**: vocabulary, cadence, bluntness, humour, digressions,
admissions, profanity, level of polish.
+ - Author authority: Is the author an experienced practitioner? Protect their authority.
- Format, audience, and genre row from the table above.
- Dose.
- If format, audience, or goal is unknown in any mode, ask the single combined question before
- proceeding - who is this for, and what should they take away? - then redo these notes if the
- answer changes the genre row or dose. Collect any further author questions as you work and ask
- them once, batched, before editing begins.
-
Anything you cannot attribute to a rule below stays exactly as written. That is the default,
not a fallback.
### 1. Run the mechanical scan
- Countable. Run before making judgment calls. The full 15-check list with thresholds and
- reasoning lives in `references/detection-rubric.md` and is canonical; this table is the
- working subset.
+ Countable. Run before making judgment calls. Thresholds and reasoning in
+ `references/detection-rubric.md`.
| Check | Flag when |
|---|---|
| Em dashes | above the genre budget, or any cluster |
- | Sentence-length spread | standard deviation under 4 words per 100-sentence window; on shorter texts use the same-length-runs check instead |
+ | Sentence-length spread | standard deviation under ~4 words over a 100-sentence window |
| Consecutive same-length runs | 3+ sentences within 5 words of each other |
| Sentence-opener repetition | over half a paragraph's sentences start with The / This / It / In |
- | Paragraph-opening transitions | over half the paragraphs open with a connective |
| Formal transitions | more than ~8 per 1,000 words |
| Hedging density | over ~5% of words |
- | Passive constructions | over ~30% of sentences, and no register reason keeps them |
+ | Passive constructions | over ~30% of sentences |
| Rule-of-three lists | any list of exactly three near-synonyms |
| Paragraph-length uniformity | most paragraphs within one sentence of each other |
- | Phrase repetition | any phrase repeated within 500 words |
| Unsourced authority | "experts agree" / "studies show" with no name |
- | Specificity floor | a paragraph describing a practice, cost, or claim with no number, name, date, or measurable quantity |
-
- Scan scope: exclude quoted examples, blockquotes presented as exhibits, and code fences from
- every count. If a protected region contains live slop, say so under `Not flagged` with the
- reason. Measurement conventions - windows, units, thresholds - are pinned in
- `references/detection-rubric.md`; follow them exactly so two readers get one answer.
-
- Steps 1 to 5 are scans: record findings, fix nothing yet.
+ | Specificity floor | any paragraph with no number, name, date, or measurable quantity |
- **Scan mechanically, never fix mechanically.** A find-and-replace across a draft produces
- sentences that are grammatical and wrong, because the right substitute differs by clause. Fix
- per occurrence. This skill's own reference files were damaged exactly this way once.
+ **Scan mechanically, never fix mechanically.** Fix per occurrence.
### 2. Run the pattern scan
- `references/structural-patterns.md`. The shapes that survive model updates, each with a bad
- example and the rewrite. Highest-yield, by corpus frequency:
+ `references/structural-patterns.md`. The shapes that survive model updates:
- - **Negative contrast.** "It's not X, it's Y". The most model-characteristic sentence shape.
- State Y.
- - **Participial pseudo-analysis.** Trailing `-ing` clauses that pretend to interpret:
- "highlighting the importance of", "underscoring the shift".
+ - **Negative contrast.** "It's not X, it's Y". The most model-characteristic sentence shape. State Y.
+ - **Participial pseudo-analysis.** Trailing `-ing` clauses that pretend to interpret: "highlighting the importance of", "underscoring the shift".
- **Significance inflation.** "stands as a testament", "marks a pivotal moment". State the fact.
- **Copula avoidance.** "serves as", "represents" where "is" is clearer.
- **Throat-clearing and faux-insight openers.** "Here's the thing", "What most people get wrong".
+ - **Downplaying others.** "Most developers do X, but I do Y", "unlike casual prompt toys". Cut the sneer. True authority is quiet; focus on domain constraints.
+ - **Failure-framing in headings.** "Why X breaks down / fails". Reframe around domain constraints.
+ - **Jargon theater.** Reject aerospace/finance cosplay ("cockpit", "tranches", "accretion drift"). Use plain technical English ("dashboard", "clearing timeline Phase 1/Phase 2").
- **Summary-recap endings.** "In conclusion", or a final paragraph restating the piece.
- **Fake-profound kickers.** The closing aphorism. Delete it, do not improve it.
### 3. Run the vocabulary scan
`references/banned-vocabulary.md`. Tier 1 replaces on sight. Tier 2 flags only when 2+ appear in
- one paragraph. Tier 3 is context-dependent and often legitimate.
+ one paragraph. Tier 4 flags Jargon Theater on sight.
**When you remove a flagged word, rewrite the sentence.** Swapping in a synonym leaves the
machine sentence intact with different paint.
### 4. Run the formatting scan
`references/formatting-tells.md`. Emoji headings, bold mid-sentence, the numbered-bold-colon
list shape, bullets where prose reads better, smart quotes pasted from a chat window, leftover
placeholders and citation markup.
- If the draft contains fenced code, also run `references/code-slop.md` against the code layer
- under the current dose: comment, name, and docstring fixes ride the vocabulary tier;
- refactoring- and testing-tier work waits for an opted-in heavy pass and says so.
-
### 5. Apply the portability test
Swap the company, person, product, and country. If the sentence survives unchanged, it is
filler. Replace it with a fact, mechanism, number, consequence, or judgment specific to this
subject, or cut it.
- Highest-leverage single test in the skill. Most slop is not badly written. It is *unattached to
- anything*.
-
- **Now apply the fixes, once, in priority order:** content-level failures first (portability,
- abstraction, unsourced claims), then paragraph and sentence shapes, then vocabulary, then
- formatting trivia. A pass that spends its effort on dashes while leaving filler sentences
- untouched has its priorities inverted.
-
### 6. Put the person back
- **The half everyone skips.** After the fixes the draft is clean and often dead. Steps 1 to 5
- are subtraction; this is the only step that adds. A draft that has been through subtraction
- alone is not finished, it is bleached.
-
- **Read `references/preserving-voice.md` before doing this step.** It catalogues the eight things
- an editing pass reliably destroys, with verbatim examples of what is at stake. The short version:
- an AI pass optimises for clarity, confidence, and inoffensiveness, while distinctive writing
- depends on timing, admitted uncertainty, and calculated risk. Those are in direct tension, and
- the pass will resolve the tension the wrong way unless you stop it.
-
- The eight, as a checklist against your own diff: pacing fragments · self-undermining hedges ·
- digressive parentheticals · named people in vulnerable disclosures · deliberate repetition ·
- unresolved endings · one-off register breaks · self-deprecation that is actually a claim.
-
- For each one you removed, answer: **was this an error, or was this the person?** If you cannot
- tell, leave it in and flag it.
-
- Work from what the source supports. Never invent an anecdote, statistic, or opinion the author
- did not have.
+ **Read `references/preserving-voice.md` before doing this step.**
+ Ensure you avoid the Twin Ditches:
+ - Do NOT retreat into academic whitepaper slop (passive voice, royal "we").
+ - Do NOT force performed incompetence on a senior engineer. Protect Quiet Technical Authority.
- - **Restore the specific.** Where you cut a vague claim, ask the author for the real number
- rather than leaving a hole. A gap is better than a lie, but the fact is better than both.
- - **Vary rhythm on meaning.** Mix 4-to-10-word sentences with 25-to-36-word ones, driven by what
- each sentence does, not by a target statistic. Forced fragments between long sentences are
- their own tell.
- - **Let paragraphs be uneven.** Some one sentence, some six. Important sections get space,
- standard sections compress, empty sections get deleted.
+ - **Restore the specific.** Real numbers, real code, real laws.
+ - **Vary rhythm on meaning.** 2–4 sentence narrative paragraphs.
- **Keep contractions.**
- - **Keep the edge.** Strong opinions, blunt language, humour, profanity, self-interruptions, and
- honest admissions, where they belong to the author.
- - **Keep the admissions.** "I got this wrong for a year", "I still don't fully understand why".
- These are the least fakeable thing in writing and the first thing an AI pass deletes.
- - **Keep the digressions** that serve the voice even when they do not serve the argument.
- - **Let sections end without a bow.** Not everything needs a closing line.
- - **Repeat the plain word** rather than rotating synonyms.
- - **Take the position.** If the draft surveys options and closes by noting what the analysis
- "raises", say which one you would pick. If the author's view is unclear, ask.
-
- `references/worked-examples.md` shows this end to end, including a case where the correct output
- is "leave it alone".
+ - **Keep first-person ownership.** ("I built", "I architected").
+ - **Take the position.** State choices clearly.
### 7. Self-check before output
- Re-run the mechanical scan on your own output. Then read it aloud, because AI rhythm is audible
- where it is invisible on screen.
-
- Then answer the two integrity questions, in this order:
-
- 1. **What still sounds AI-generated?** Fix what you find.
- 2. **Did the rewrite add or remove any fact, name, number, date, quote, or claim?** Treat an
- unsupported addition and a silently lost claim as the same class of error. Restore or flag.
-
- If a mechanical check still fails after one fix round, either run at most one more round or
- report the residual in the output. Two rounds is the hard bound; do not loop silently, and do
- not stop while a known failure is unmentioned.
+ Re-run the mechanical scan on your own output. Then read it aloud.
- Final question: **would the author recognise this as their own writing?** Cleaner but no longer
- theirs means you over-corrected. Go back to Step 6.
+ Final question: **would the author recognise this as their own writing?**
## Hard rules
- Never change what is claimed. Only how it is said.
- - Never rewrite quoted material, titles, or text being discussed rather than used. If a draft
- quotes slop as an example, the example stays slop.
- Never invent a fact, statistic, source, quote, or opinion to replace a vague one. Flag it.
- - Never soften or inflate a claim. "Around 40%" stays "around 40%". "I think it might work"
- stays a maybe. Deleting an honest hedge to sound authoritative is a lie about confidence.
- - Never output a verdict on whether a human or a model wrote something.
- - Never replace an em dash with a hyphen, en dash, or double hyphen. Swapping one dash glyph
- for another trades the tell instead of removing it. Use a period, comma, or parentheses,
- chosen per clause.
+ - Never downplay other developers or treat peers as inferior ("most developers use toys").
+ - Never frame headings around others "failing" or "breaking down"; frame around domain constraints.
+ - Never strip senior technical authority or replace confident first-person singular ("I built") with detached academic third-person ("the system was evaluated") or the royal "we".
+ - Never replace an em dash with a hyphen. Use a period, comma, or parentheses.
- Never restructure an argument on a light or medium dose.
- Cutting must be proportional to the actual slop.
## Output format
- Two shapes come before the template:
-
- - **Zero-change.** The scan finds nothing failing and the draft reads fine: return a short
- verdict, optional notes under `Needs you`, and the line `No edit made.` (Example 3's shape.)
- Never render template sections with nothing in them.
- - **Husk draft.** If subtraction would remove more than half the draft, or every surviving
- sentence needs an author-supplied fact, do not ship the remains. Return the patterns found,
- the `Needs you` list, and stop. An emptied draft is not an edited one.
-
**Improve mode**
```
[full edited draft]
## What changed
Dose: [light / medium / heavy]
- [pattern removed], N instances
- [structural change], and why
## Left alone deliberately
- [voice trait], and why it stays
## Needs you
- [any claim I cut or flagged that needs a real number or source]
```
**Audit mode**
```
## Patterns found
1. [Pattern name] · "quoted line" → fix in a few words
## Mechanical scan
[checks that failed, with counts]
## Not flagged
[voice traits that look deliberate and should be protected]
```
## Done =
The writing is better, the author would still recognise it as theirs, every rule-triggered
- pattern is either fixed or consciously kept with a stated reason, anything that needed a real
- fact is flagged rather than invented - or the scan came back clean and the correct output was
- no edit at all.
+ pattern is either fixed or consciously kept with a stated reason, and anything that needed a
+ real fact is flagged rather than invented.