ig-humanizer ยท diff
git:20260730.2b4f2cb to git:20260905.9b284f7
190 added, 37 removed. Audit A to A.
---
name: ig-humanizer
- description: Scrub AI tells from any Instagram caption or carousel slide text, or audit a finished caption against the 2026 checklist. Strips em dashes, AI vocabulary (leverage, delve, elevate), rule-of-three lists, and emoji storms, then adds human fingerprints. Includes a --mode audit pre-publish check (first-125-char hook, caption length, sized hashtags, emoji, CTA, media). Triggers on humanize, de-AI my caption, audit before posting. Not for writing from scratch (use ig-caption-writer or ig-carousel-planner).
+ description: 'Remove the AI tells readers react to in an Instagram caption or carousel slide: 2026 vocabulary by density, reveal bridges, staccato stacks, stacked triads, performed sincerity, emoji storms; caps em dashes. Includes --mode audit (first-125 hook, length, hashtags, emoji, CTA, media) and --mode profile. Not for beating AI detectors (no edit reliably does). Not for writing from scratch (use ig-caption-writer or ig-carousel-planner). Keywords: humanize, de-AI caption, audit before posting.'
---
- # Instagram Humanizer
+ # Instagram Humanizer V3
- Rewrites any caption or carousel slide text to remove AI tells, and audits a
- finished caption against the 2026 Instagram checklist. Based on Wikipedia's
- "Signs of AI writing" taxonomy plus Instagram-specific patterns (the first-125
- fold, the lowercase-casual caption register, sized hashtags, sends-and-saves
- structure).
+ Rewrites any caption or carousel slide text to remove the AI tells that human
+ readers notice, and audits a finished caption against the 2026 Instagram
+ checklist. Based on Wikipedia's "Signs of AI writing" taxonomy, the 2025-2026
+ stylometry literature, our own Instagram caption corpus (n=284, prevalence
+ only), and Instagram-specific patterns (the first-125 fold, the
+ lowercase-casual caption register, sized hashtags, sends-and-saves structure).
+ **V3 (2026-09):** recalibrated on 2026 evidence. Vocabulary is scored by
+ density, em dashes are capped instead of banned (and the cap is generous here:
+ 29% of human captions use one), 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 caption-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 on Instagram a
+ caption that reads as a brand account earns neither the save nor the send.
+ 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; [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 appears in 10% of human
+ captions in our corpus [strong], so 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 [strong], and **29% of human Instagram captions
+ contain one** [strong: corpus]. A caption's em dash is never a tell on its
+ own, and a blanket ban over-sterilises captions. New rule: cap at about 1 per
+ 100 words (1-2 per caption), replace only the excess with a comma, colon,
+ parentheses or a rewrite. Never a period (a split dash stacks fragments).
+ Zero em dashes across a long caption is its own tell now.
+ - **Forced burstiness is the #1 2026 tell, not the fix.** Mechanical
+ long/short alternation is a learnable humanizer fingerprint [weak], and
+ "Short. Punchy. Done.", "No X. No Y. Just Z.", one-word lines for drama and
+ "The result?" reveals are the current top reader-cited tells [strong].
+ Captions are mid-length, so Pass 2 is an anti-uniformity guard only: fix a
+ paragraph that reads machine-flat, never manufacture variance.
+ - **Rule of three is still a tell, at density.** Tricolon runs at 2x
+ expert-human rate across 2026 frontier models [strong], and 23% of human
+ captions contain one [strong: corpus]. So one natural triple with concrete
+ items stays. Stacked, perfectly parallel or hollow triads and a third triad
+ in a caption get scrubbed.
+ - **Fingerprint injection was half wrong.** Named entities and concreteness are
+ supported [strong]; an odd-precision number with a referent in the first 125
+ chars is the strongest hook. 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", "real
+ talk", "POV:" on something that is not a POV) 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 caption or carousel (rewrite mode)
- Pre-publish review of a finished caption (audit mode, see `sub-skills/post-audit.md`)
- When a caption feels off and you cannot pinpoint why
## Input
Any text: a caption, the on-image text of a carousel, or a Reel caption.
Optional: target voice samples (the user's past captions).
## Output
- Rewritten text with AI tells removed
- A diff showing what changed and why
- Caption char count (flagging if the hook spills past the first 125 chars)
- - Confidence: "human", "mixed", "AI-likely"
+ - 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
```bash
- # Default: scrub AI tells and fix Instagram-format issues
+ # Default: scrub AI tells (forensic + strict) and fix Instagram-format issues
ig-humanizer <text>
# Forensic only - minimum touch, just kill model leakage
ig-humanizer --mode forensic <text>
# Audit - detection-only pass-fail review, no rewrite
# Runs the 2026 Instagram checklist: first-125 hook, caption length, sized
# hashtags, emoji limits, CTA quality, media reminder.
# Returns Blockers + Warnings + suggested fixes. See sub-skills/post-audit.md.
ig-humanizer --mode audit <text>
+
+ # Profile - build/update the user's Voice & Brand Profile. See the section below.
+ ig-humanizer --mode profile
```
- ## The three passes
+ ## The four passes
- ### Pass 1 - SCRUB (delete or replace)
+ ### Pass 1 - SCRUB (score, then delete or replace)
- Apply the tiered catalogs in `references/scrub-rules.md`:
+ Apply the tiered catalogs in `references/scrub-rules.md`. The unit of
+ judgement is the **paragraph (or slide), not the word**: count markers per
+ paragraph, rewrite the paragraph 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 dash overuse.
- - **Strict** (default on): bad Instagram style regardless of origin. Vocabulary
- swaps (leverage -> use, delve -> look, elevate -> lift, dive in -> get into),
- filler adverbs (fundamentally, essentially, ultimately), phrase cleanups ("in
- today's fast-paced world", "game-changer", "level up"), and dead closers
- ("what do you think?", "double tap if you agree").
+ of my last update"), template blanks ([Your 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"), 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 caption,
+ phrase cleanups ("in today's fast-paced world", "game-changer", "level up",
+ "dive in"), emoji storms, and dead closers ("what do you think?", "double
+ tap if you agree").
+ - **Instagram-format scrubs** (always apply): first-125 hook that stands
+ alone, sized hashtags, emoji limits, carousel slide-1 promise, caption
+ length.
- ### Pass 2 - BREAK (force burstiness)
+ ### Pass 2 - RHYTHM (anti-uniformity guard only)
- - Vary line length. A caption where every line is the same length reads as a
- machine. Break at least one into a short punch line.
- - Add a sentence fragment where it fits ("every time.").
- - Break perfect parallel structures with one asymmetric line.
+ Detectors do not score burstiness, and captions are mid-length (our corpus
+ median is well under 200 words), so rhythm is neither a reach lever nor a
+ fix. What readers notice is the mechanical-uniformity tell (every line the
+ same length, machine-flat) 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.
+ - 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 caption, total. "every time." once is a
+ voice quirk. Three in a caption 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 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. One idea per line with blank lines between them is
+ native caption formatting and stays. Fragment-for-drama inside those lines
+ is the tell. Keep the layout, fix the sentences.
+ - Carousel slide text is short by design; never chop or pad a slide for
+ rhythm. Never alternate long/short/long/short across slides or lines. 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:
- - 1 specific number (replace "many", "a lot", "tons")
- - 1 named entity (real person, company, tool)
- - the lowercase-casual register if the voice calls for it
- - 1 first-person concrete detail
+ - One odd-precision number WITH a named referent: who, what, when, or what it
+ cost ("0 to 10k in 4 months, posting 3 times a week", not "grew fast" and not
+ "10k"). A bare number is not a fingerprint; the referent carries the signal.
+ - One named entity (real person, brand, date, tool)
+ - One first-person concrete detail (what you saw, what it cost, what broke)
+ - One specific, dated, uncomfortable fact stated flat, with no framing sentence
+ before or after it. Not "real talk, this one hurt: I lost the client." Just
+ "I lost my biggest client on 14 Feb." The fact carries the vulnerability. The
+ frame turns it into performed sincerity, which readers now read as the tell.
+ - The lowercase-casual register if the voice calls for it
- If the input lacks these, ask the user for a number or anecdote. Do not fabricate.
+ 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, "POV:" on
+ something that is not a POV. 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.
+ 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, 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, every em dash gone, every triad gone, every emoji
+ gone from a voice that uses them, the lowercase register capitalised? If
+ yes, restore what the author had. Zero em dashes and zero triads in a long
+ caption 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 caption 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:
+ rules (V3):
- **Scrubbing is always in scope.** When asked to humanize, de-AI, finalize, or
publish a caption, 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 corporate-speak, filler openers,
- or AI-tell phrasing. Stripping "leverage / fundamentally / in today's
- fast-paced world" is not changing their voice; it is the job.
+ voice quirks and what they are claiming, NOT reveal bridges, staccato stacks,
+ 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.
- - Keep the user's voice quirks (lowercase starts, `..` soft pauses).
+ - 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 per ~100 words, one natural triad, their 1-3 intentional emoji).
+ - Never promise detector results. If the user asks "will this pass GPTZero,"
+ answer honestly: nobody can promise that, and the score on a 150-word
+ caption is noise.
- Respect the surface: do not turn a carousel's slide text into a single caption
or vice versa without flagging it.
- Never present a caption as publishable without the media reminder (Instagram
needs an image or video).
## Instagram-specific tells this skill catches
- A hook that needs the second line to make sense (the "more" fold eats it).
- - A caption opening with "Let's talk about.." or "Here's the thing..".
+ - A caption opening with "Let's talk about..", "Here's the thing..", or "POV:"
+ on something that is not a POV.
- 20-30 hashtags crammed at the top instead of a 3-5 sized set.
- Emoji sprinkled through every line (4+ per caption).
- A bare title on carousel slide 1 instead of a promise + loop.
- - Rule-of-three lists with no specifics ("faster, cheaper, better").
+ - Stacked or hollow rule-of-three lists ("faster, cheaper, better"); one
+ natural triple with concrete items is fine.
- Engagement bait ("comment YES", "tag 3 friends", "double tap if").
- - Uniform line lengths (machine rhythm).
+ - Staccato stacks and one-word lines for drama (the humanizer fingerprint), or
+ a paragraph where every line reads machine-flat.
## Example
See `references/examples.md` for worked before/after rewrites.
## Files
- `SKILL.md` - this file (rewrite scrubber + audit-mode entry)
- - `references/scrub-rules.md` - vocabulary swaps and regex by tier
+ - `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 captions and slides
- `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`)
`ig-humanizer --mode profile` builds or updates the user's Voice & Brand Profile at `../../references/voice-profile.md` from 3-6 of their real Instagram 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
- `ig-caption-writer` - generates captions that already pass the humanizer
- `ig-carousel-planner` - generates carousels that already pass the humanizer