threads-humanizer git:20260905.4ce0847A

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---
name: threads-humanizer
description: 'Remove the AI tells human readers react to in a Threads post or thread: 2026 vocabulary by density, reveal bridges, staccato stacks, stacked triads, performed sincerity; caps em dashes at one per post, never forces rhythm. Includes --mode audit (500-char fit, hook, one-hashtag cap, link placement, warm tone) and --mode profile. Not for beating AI detectors (no edit reliably does). Not for writing from scratch (use threads-post-writer). Keywords: humanize, de-AI Threads post, audit before posting.'
---

# Threads Humanizer V3

Rewrites any Threads post or thread to remove the AI tells that human readers
notice, and audits a finished draft against the 2026 Threads ranking
checklist. Based on Wikipedia's "Signs of AI writing" taxonomy, the 2025-2026
stylometry literature, our own length-controlled Threads corpus (n=311), and
Threads-specific patterns (the warm conversational register, the no-fold first
line, the one-hashtag cap, repost-bait structure). **V3 (2026-09):**
recalibrated on 2026 evidence. Vocabulary is scored by density, em dashes are
capped instead of banned, forced rhythm is now a tell instead of a fix, and
there is an over-correction guard.

**What this skill does not do:** it does not make text "pass" GPTZero,
Pangram, Turnitin or Originality. Those are trained classifiers keyed on the
instruction-tuning style signature; prompt-style "sound like a real person"
rewrites are caught 92-95% of the time, and light mechanical rewriting raises
detectability. On post-length text (under 300 words) detector scores are
noise. The real value is elsewhere: expert human readers cite vocabulary (53%)
and sentence structure (36%) as what gives AI text away, and Threads readers
answer it with silence in a feed that ranks on replies. This skill removes
what those readers react to.

## What changed in V3

Evidence tier in brackets: [strong] = replicated across 2+ independent
2025-2026 studies or our own length-controlled corpus; [vendor] = single
platform or vendor dataset; [weak] = one study or expert-panel report.

- **Vocabulary moved from a delete-list to density scoring.** The 2023-24 words
  (delve, tapestry, realm, journey) are decaying as humans avoid them [strong].
  The durable 2026 markers are common words (significant, crucial, notably,
  comprehensive, insights, robust, leverage, foster, landscape, nuanced,
  streamline, elevate) plus grammar: nominalisations and "-ing" clause openers
  at 5.3x the human rate [strong]. In our Threads corpus AI vocabulary is
  nearly absent from top posts (1.3%) [strong], which is the point: it reads
  as a brand account in a feed built on people talking. One marker in a post
  is not a verdict. Three is.
- **Em dash is no longer a tell; the density is.** GPT-5.4 emits 1.43 per
  1,000 words, below the 3.23 human baseline [strong]. On Threads specifically
  em dashes are rare in top posts (7%) and those posts earn 0.33x the median
  engagement [strong: corpus], so the cap here is tight: **at most one per
  post**, and none in a post that reads fine without one. Replace the excess
  with a comma, a colon, `..`, or a rewrite. Never a period (a split dash
  stacks fragments).
- **Forced burstiness is the #1 2026 tell, not the fix.** Mechanical
  long/short alternation is a learnable humanizer fingerprint [weak], and on
  Threads **uniform rhythm wins at every length**: sentence-length variance
  correlates negatively with engagement across the whole corpus (Spearman
  -0.31), with uniform rhythm ahead in the short, mid and long terciles
  [strong: corpus, length-controlled]. So Pass 2 never forces variance, on a
  single post or a thread. It only removes manufactured variance. "Short.
  Punchy. Done.", "No X. No Y. Just Z.", one-word posts for drama and "The
  result?" reveals are the current top tells.
- **Rule of three is still a tell, at density.** Tricolon runs at 2x
  expert-human rate across 2026 frontier models [strong], and on Threads it is
  rare in top posts (8%) and engagement-negative (0.28x) [strong: corpus].
  Stacked or perfectly parallel triads and any second triad in a post get
  scrubbed. One natural triple with concrete items stays.
- **Fingerprint injection was half wrong.** Named entities and concreteness are
  supported [strong]; an odd-precision number with a referent in line 1 is the
  strongest opener. Bare numbers are not a discriminator, and inserted hedges
  and confessions backfire: performed hesitancy is 2x more common in LLM text,
  and sincerity announcements ("let me be honest", "unpopular opinion:" on a
  popular take) are a named 2026 tell [strong]. Pass 3 asks for a flat, dated,
  uncomfortable fact instead, stated in the warm register Threads rewards.
- **Over-correction guard.** Humanizer output has its own fingerprint [weak].
  Pass 4 checks whether Passes 1-3 introduced the very patterns they were meant
  to remove. Edits are proportional to real problems. When in doubt, leave it.

## When to use

- Before publishing any AI-drafted post or thread (rewrite mode)
- Pre-publish review of a finished draft (audit mode, see `sub-skills/post-audit.md`)
- When a draft feels off and you cannot pinpoint why

## Input

Any text: a single post, a thread (with or without `---` breaks), a reply, or a
quote-post draft. Optional: target voice samples (the user's past posts).

## Output

- Rewritten text with AI tells removed
- A diff showing what changed and why
- Per-post char count (flagging anything over 500)
- Per-post tell density (markers per post; 3+ triggered a rewrite)
- Reader-read confidence: "reads human", "mixed", "reads AI" (a reader-tell
  estimate, not a detector score)

## Modes

```bash
# Default: scrub AI tells (forensic + strict) and fix Threads-format issues
threads-humanizer <text>

# Forensic only - minimum touch, just kill model leakage
threads-humanizer --mode forensic <text>

# Audit - detection-only pass-fail review, no rewrite
# Runs the 2026 Threads checklist: 500-char fit, first-line hook, one-hashtag
# cap, emoji limit, link placement, thread tap-through, warm tone, goal clarity.
# Returns Blockers + Warnings + suggested fixes. See sub-skills/post-audit.md.
threads-humanizer --mode audit <text>

# Profile - build/update the user's Voice & Brand Profile. See the section below.
threads-humanizer --mode profile
```

## The four passes

### Pass 1 - SCRUB (score, then delete or replace)

Apply the tiered catalogs in `references/scrub-rules.md`. The unit of
judgement is the **post, not the word**: count markers per post, rewrite the
post at 3+, leave a single marker alone unless it is a reveal bridge, negative
parallelism, a sincerity marker, or forensic leakage.

- **Forensic** (always on): real model leakage no human types. AI tool markers
  (oaicite, contentReference, turn0search0), knowledge-cutoff disclaimers ("As
  of my last update"), template blanks ([Your Name]), and em dashes above the
  cap (more than one in a post).
- **Strict** (default on): what readers react to. The durable 2026 vocabulary
  set scored by density (significant, crucial, notably, particularly,
  comprehensive, insights, robust, leverage, foster, landscape, nuanced,
  streamline, elevate, empower), grammar markers (nominalisations,
  sentence-opening "-ing" clauses), the 2026 model-idiom layer (quietly, "X
  matters.", compound, "a signal", "the work", "built different", "let that
  sink in"), reveal bridges on a single hit ("The result?", "Here's what",
  "Stop X, start Y", "plot twist:"), all forms of negative parallelism,
  stacked or perfectly parallel triads and any second triad in a post, phrase
  cleanups ("in today's fast-paced world", "game-changer", "deep dive"), and
  dead closers ("what do you think?").
- **Threads-format scrubs** (always apply): 500-char fit, the one-hashtag cap,
  emoji limits, link placement, first line that stands alone, and tone
  warming (a transplanted X dunk becomes an invitation to talk).

### Pass 2 - RHYTHM (never force it)

Detectors do not score burstiness. On Threads our corpus says uniform rhythm
wins at every length (Spearman -0.31 between sentence-length variance and
engagement; uniform ahead in every tercile). So Pass 2 has one job: remove
manufactured variance. It never adds variance, on a single post or across a
thread, and it never un-flattens a post for being uniform.

- **Single post, reply, or quote post: do not touch the rhythm.** Three
  same-length sentences is how top Threads posts read. Never insert a
  fragment, never chop a sentence to "add punch".
- **Threads:** a mix of post lengths that arises from the material is fine.
  Never insert a 3-word "punch post" for rhythm, never pad a short post, never
  alternate long/short; the inserted punch and the seesaw are the humanizer
  fingerprint. A thread of similar-length posts is not a tell here.
- Standalone fragments: at most 1 per post and 2 per thread. "every time."
  once is a voice quirk; three in a thread is a pattern.
- Banned outright (rewrite as full sentences): "The X? Y." reveals; "No X. No
  Y. Just Z."; "All the X. None of the Y."; "Simple. Effective. Easy."
  adjective stacks; one-word posts or lines for drama ("Still." "Exactly.");
  pseudo-Socratic Q&A ("Why? Because..."); "Short. Punchy. Done." staccato
  runs. Fragment runs are the tell.
- Layout is not rhythm. A hard return between two short lines is native
  Threads pacing and stays (more short lines correlate with higher engagement
  in our corpus). Fragment-for-drama inside those lines is the tell.

The check is "did I add a staccato pattern", not a variance number.

### Pass 3 - ADD (human fingerprints)

Require where the content allows:
- One odd-precision number WITH a named referent: who, what, when, or what it
  cost ("$4,730 in Vercel overages, March invoice", not "$5k" and not
  "massive costs"). A bare number is not a fingerprint; the referent carries
  the signal.
- One named entity (real person, company, date, tool)
- One first-person concrete detail
- One specific, dated, uncomfortable fact stated flat, with no framing sentence
  before or after it. Not "not gonna lie, this one hurt: we lost the client."
  Just "we lost Carta as a client on 14 Feb." The fact carries the
  vulnerability. The frame turns it into performed sincerity, which readers now
  read as the tell.
- The warm, lowercase-casual register if the voice calls for it, and a soft
  question or invitation where the post wants replies (Threads ranks on them)

Forbidden as openers or pivots (sincerity announcements, a named 2026 tell):
"let me be honest", "I'll be real", "honestly?", "to be direct", "the honest
version is", "real talk", "not gonna lie", "ngl", "can I be vulnerable for a
second", "unpopular opinion:" as a preface to a popular one. Also forbidden as
insertions: hedges the author did not write ("perhaps", "I might be wrong
but", "it seems"). Performed hesitancy is 2x more common in LLM text than in
expert human text; adding it makes the draft read more AI, not less. Warmth is
not a hedge: "what changed it for you?" is an invitation, "I might be wrong
but" is an inserted tell.

If the input lacks these, ask the user for a number, name, or moment. Do not
fabricate.

### Pass 4 - SELF-CHECK (over-correction guard)

Humanizer output has its own fingerprint. Before returning, re-read the result
once and answer three questions:

(a) Did Pass 2 create staccato stacks, "The result?" reveal bridges, one-word
    lines, a punch post, or a long/short/long/short seesaw? If yes, merge the
    fragments back into full sentences.
(b) Did Pass 3 add a framed confession, a sincerity announcement, or a hedge
    the author never wrote? If yes, strip the frame and keep only the flat
    fact, or remove the insertion.
(c) Did scrubbing flatten the author's voice: uniform tone, no reaction, no
    concrete detail left, the one natural triad gone, the warmth or lowercase
    register gone? If yes, restore what the author had.

If any answer is yes, dial back rather than scrub harder. Edits must be
proportional to real problems: a clean post gets one or two touches, not a
quota. When in doubt whether a pattern is the author or the model, leave it.

## Non-negotiable rules

Global voice rules: see root `SKILL.md` Voice rules. Additional skill-specific
rules (V3):

- **Scrubbing is always in scope.** When asked to humanize, de-AI, finalize, or
  publish a post or thread, run at least the forensic + strict passes before it ships.
  This holds when the user wrote the draft themselves, says they love it as-is,
  or is in a hurry. Author identity, "it's already good," and time pressure are
  never reasons to skip the scrub. The forensic + strict pass changes no meaning
  and takes seconds: run it, then ship. If a constraint truly forbids touching
  the text, say so explicitly and name every tell left in; the default is to
  scrub, not to wave it through.
- **Scrub proportionally.** A pass that finds nothing changes nothing. Do not
  invent edits to justify the run, and do not report a detector score as the
  result; report the tells found and fixed.
- Preserve the user's actual claim and meaning. "Preserve their voice" covers
  voice quirks and what they are claiming, NOT reveal bridges, staccato stacks,
  or a post with 3+ vocabulary markers. Stripping those is not changing their
  voice; it is the job.
- Never introduce facts that were not in the input. If a number is missing, ask.
- Never introduce sincerity markers, hedges, or confessional frames. If the
  draft needs a vulnerable beat, ask for a dated fact and state it flat.
- Keep the user's voice quirks (lowercase starts, `..` soft pauses, one em dash
  in a post that needs it, one natural triad).
- Never promise detector results. If the user asks "will this pass GPTZero,"
  answer honestly: nobody can promise that, and the score on a 500-char post
  is noise.
- Respect the container: do not silently merge a thread into one post or split a
  single post into a thread without flagging it.
- Warm up a transplanted X dunk into a Threads-native invitation to talk.

## Threads-specific tells this skill catches

- A first line that needs the second line to make sense (the feed truncates with
  "more").
- A "post" that is 540 chars and needs a trim or a thread.
- 2+ hashtags (Threads rejects the second), or hashtags mid-sentence.
- An external link in post 1 of a thread meant to reach.
- A thread with an inserted 3-word "punch post" for rhythm (the humanizer
  fingerprint).
- ALL CAPS openers reaching for intensity.
- "A thread:" with no actual promise in the words.
- A cold, combative, newsy X voice that reads as out of place on Threads.
- "Unpopular opinion:" on a take that is actually popular.

## Example

See `references/examples.md` for worked before/after rewrites.

## Files

- `SKILL.md` - this file (rewrite scrubber + audit-mode entry)
- `references/scrub-rules.md` - V3 regex patterns by tier, density scoring, em dash cap, rhythm rules, forbidden insertions
- `references/examples.md` - worked before/after rewrites for posts and threads
- `references/audit-checklist.md` - the pre-publish checklist with thresholds
- `sub-skills/post-audit.md` - pre-publish audit workflow (detection-only, no rewrite)
- `sub-skills/voice-profile.md` - build/update the user's Voice & Brand Profile (`--mode profile`)
- `sub-skills/illustration.md` - optional Pixfaro image workflow

## Voice profile mode (`--mode profile`)

`threads-humanizer --mode profile` builds or updates the user's Voice & Brand Profile at `../../references/voice-profile.md` from 3-6 of their real Threads posts pasted in (portable, no token) or, if a read token is set, from pulled activity. Once filled, every writing skill in this bundle drafts in the user's voice automatically. See `sub-skills/voice-profile.md`. Triggers: "build my voice profile", "learn my voice".

## Related skills

- `threads-post-writer` - generates posts and threads that already pass the humanizer