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

# 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