Facebook Page Humanizer V3

Rewrites any Facebook Page post to remove the AI tells that human readers notice, and audits a finished draft against the 2026 Facebook ranking checklist. Based on Wikipedia's "Signs of AI writing" taxonomy, the 2025-2026 stylometry literature, and Facebook-Page-specific patterns (the under-80 sweet spot, the "See more" fold, the "We are thrilled to announce" corporate tell, and the meaningful-interactions model). 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. Facebook has no corpus of its own yet, so the calibration follows the LinkedIn one (the closest long-and-short mixed feed).

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 a Page post that reads as a bot earns neither the share nor the comment Facebook's meaningful-interactions model ranks on. 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 corpus on sibling platforms; [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]. AI vocabulary is the one marker consistently reach-negative on the sibling platforms we measured [strong]. One marker in a paragraph is not a verdict. Three is.
• Em dash is no longer a tell. GPT-5.4 emits 1.43 per 1,000 words, below the 3.23 human baseline; 23-29% of human posts and captions on sibling platforms use one [strong]. Zero em dashes is now its own tell (the writer is trying to look human). New rule: cap at about 1 per 100 words (so 0-1 in a short post, 1-2 in a story post), replace only the excess with a comma, colon, parentheses or a rewrite. Never a period.
• Forced burstiness is the #1 2026 tell, not the fix. Mechanical long/short alternation is a learnable humanizer fingerprint [weak], and on the platforms we measured sentence-length variance is not an engagement lever in either direction (LinkedIn within-creator: null; Threads: uniform wins) [strong]. "Short. Punchy. Done.", "No X. No Y. Just Z.", one-word lines for drama and "The result?" reveals are the current top tells. Pass 2 is now RHYTHM, not BREAK: an anti-uniformity guard only, never manufactured variance. A short Page post has nothing for Pass 2 to touch.
• Rule of three is still a tell, at density. Tricolon runs at 2x expert-human rate across 2026 frontier models [strong]. Stacked, perfectly parallel triads and 3+ per post get scrubbed. One natural triple with concrete items stays (21-39% of top human posts have one).
• 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 [vendor]. 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", "we'll be real with you") are a named 2026 tell [strong]. Pass 3 asks for a flat, dated, uncomfortable fact instead.
• 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 Page post (rewrite mode)
• Pre-publish review of a finished draft (audit mode, see sub-skills/post-audit.md)
• When a draft feels corporate or off and you cannot pinpoint why

Input

Any text: a short Page post, a longer story post, or a comment reply draft. Optional: target voice samples (the Page's past posts).

Output

• Rewritten text with AI tells removed
• A diff showing what changed and why
• Char count, with a flag when a post crosses the 80-char sweet spot
• Per-paragraph tell density (markers per paragraph; 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 Facebook-format issues
fb-humanizer <text>

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

# Audit - detection-only pass-fail review, no rewrite
# Runs the 2026 Facebook checklist: under-80 sweet spot, first-line hook,
# engagement bait, hashtag/emoji limits, link-post reach warning, goal clarity.
# Returns Blockers + Warnings + suggested fixes. See sub-skills/post-audit.md.
fb-humanizer --mode audit <text>

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

# Interview - fill the Story Bank: what you have to say, not how you say it.
# 20-40 minutes, resumable, or --mode interview post for one focused topic.
fb-humanizer --mode interview

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 paragraph, not the word: count markers per paragraph (a short post is one paragraph), rewrite the paragraph at 3+, leave a single marker alone unless it is a reveal bridge, negative parallelism, a sincerity marker, a corporate opener, 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], [Page Name]), and em dashes above the cap (more than about 1 per 100 words).
• 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"), corporate openers on a single hit ("We are thrilled to announce" becomes the plain news), 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 third triad in a post, phrase cleanups ("in today's fast-paced world", "game-changer", "deep dive"), and dead closers ("What do you think?", "Let us know in the comments below!").
• Facebook-format scrubs (always apply): the under-80 short version when the point fits, the "See more" fold, engagement bait, hashtag and emoji limits, bare-link framing.

Pass 2 - RHYTHM (anti-uniformity guard only)

Detectors do not score burstiness, and on the platforms we measured sentence-length variance is not an engagement lever in either direction. What readers notice is the mechanical-uniformity tell (every sentence the same length, machine-flat; structure is 36% of expert judgments) and, worse, the staged variance that second-generation humanizers add. So Pass 2 has two jobs: fix rhythm only where it reads machine-flat, and remove manufactured variance everywhere. It never adds variance as a tactic.

• Short post (under ~80 chars) or a comment reply: no rhythm balancing. One line has no rhythm to fix. Never split it into fragments for punch. The banned-outright patterns below still get rewritten as full sentences even in a short post ("No delays. No excuses. Just results." is a tell at any length).
• Story post: per paragraph, one genuinely long sentence next to a short one is fine and is what human variance looks like. Two or three mid-length sentences in a row are also fine. Edit only when every sentence in the paragraph runs the same length and reads flat, and then edit one sentence, not the paragraph.
• Standalone fragments: at most 2 per post, total. "Every time." once is a voice quirk. Three in a post 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 paragraphs ("Still." "Exactly."); pseudo- Socratic Q&A ("Why? Because..."); "Short. Punchy. Done." staccato runs. Fragment runs are the tell.
• Layout is not rhythm. One or two sentences per paragraph with blank lines between them is mobile-native Page formatting and stays. Fragment-for-drama inside those paragraphs is the tell. Keep the layout, fix the sentences.
• Never alternate long/short/long/short across a post. That seesaw is the humanizer fingerprint.

The check is "does any paragraph read machine-flat, and 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 ("200 loaves in a stranger's kitchen by 9", not "a lot of bread" and not "200"). A bare number is not a fingerprint; the referent carries the signal.
• One named entity (real person, business, date, place, tool)
• One first-person or behind-the-scenes concrete detail (what broke, what it cost, who showed up)
• One specific, dated, uncomfortable fact stated flat, with no framing sentence before or after it. Not "We'll be honest, this was hard: the oven died." Just "The oven died at 4am on our busiest Saturday." The fact carries the vulnerability. The frame turns it into performed sincerity, which readers now read as the tell.
• A warm, human Page voice (not a press release, not a faceless bot)

Forbidden as openers or pivots (sincerity announcements, a named 2026 tell): "let me be honest", "we'll be real with you", "honestly?", "to be direct", "the honest version is", "real talk", "full transparency", "not gonna lie", "unpopular opinion:" as a preface to a popular one. Also forbidden as insertions: hedges the author did not write ("perhaps", "we 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.

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 paragraphs, 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 Page's voice: uniform tone, no reaction, no concrete detail left, every em dash gone, every triad gone, a deliberate story post shrunk to a one-liner? If yes, restore what the author had. Zero em dashes and zero triads in a story post is a tell in its own right.

If any answer is yes, dial back rather than scrub harder. Edits must be proportional to real problems: a clean post gets two or three 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 Page post, 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, corporate openers, or a paragraph 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 Page's voice quirks (its register, its .. soft pauses, one em dash per ~100 words, 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 an 80-char post is noise.
• Respect the container: do not silently turn a deliberate story post into a one-liner, or pad a short post into a wall, without flagging it.

Facebook-specific tells this skill catches

• "We are thrilled / excited / delighted to announce.." corporate auto-pilot.
• A long post whose actual point is one short line hiding in paragraph 3.
• A first line that needs the second line to make sense (the "See more" fold).
• Engagement bait ("LIKE and SHARE if you agree", "comment YES", "tag 3 friends").
• 5+ hashtags stuffed at the bottom.
• A bare external link with no framing text.
• Generic corporate hype with no specific detail.
• Staccato stacks and one-word lines for drama (the humanizer fingerprint), or a story paragraph where every sentence reads machine-flat.
• "We'll be honest with you" framing around what should be a plain fact.

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 short and story posts
• 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/story-bank-interview.md - interview the user and fill the Story Bank (--mode interview)
• sub-skills/illustration.md - optional Pixfaro image workflow

Voice profile mode (--mode profile)

fb-humanizer --mode profile builds or updates the user's Voice & Brand Profile at ../../references/voice-profile.md from 3-6 of their real Facebook 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".

Story Bank mode (--mode interview)

fb-humanizer --mode interview interviews the user and writes ../../references/story-bank.md: the numbers, dated moments, turning points, scars and positions their posts are made of. The Voice Profile holds how they sound; the bank holds what they have to say, and an empty bank is the usual reason drafts come out generic. Budget 20 to 40 minutes, resumable across sessions.

--mode interview post runs the short version: 5 to 8 questions on one topic, ending in a five-line spine (Moment, Number, Correction, Opposition, Ask) handed to fb-post-writer.

Never invents an answer: a line with nothing real in it stays empty and the section is marked thin. See sub-skills/story-bank-interview.md. Triggers: "interview me", "ask me questions", "help me work out what to post about".

Related skills

• fb-post-writer - generates posts that already pass the humanizer
• fb-engagement-drafter - drafts comment replies the humanizer can scrub