Ai slop audit

AI-Slop Audit — Defect Analysis + Rewrite Toward Voice

Purpose

This skill does two jobs the way a good editor does: it names what makes a draft read as machine-written, and it rewrites each defect toward a real human voice — not by deleting patterns mechanically, but by replacing them with the specific, evidence-bearing, rhythmically-varied writing that AI text lacks.

It is the analysis half of "analyze the most common defects of AI-generated content, and provide the key content-creation reference." The taxonomy is the analysis; the per-defect rewrite directives are the reference.

The governing distinction: an AI tell is a pattern and a frequency, almost never a single token. Em-dashes are good writing; the tell is using them as the only rhythmic device. The rule of three is good rhetoric; the tell is using it in every paragraph. This skill therefore scores density and co-occurrence, and it never recommends a blanket ban on a punctuation mark or a word. Mechanical de-slopping (delete all em-dashes, swap every "leverage" for "use") produces stiff, lobotomized text — a different kind of bad writing. The fix is always: replace the pattern with something specific to this author and this point.

Routing — this skill vs. content-review

These two overlap on voice, so route by what the request is about:

• Run this, not content-review, when the request is about how the writing reads — "sound less like AI," "humanize this," "does this sound like ChatGPT," "remove the tells," "make it sound like a person."
• Run content-review instead when the request is about whether it should ship — ICP fit, funnel stage, CTA, differentiation, platform format, launch-readiness scoring.
• They compose: run ai-slop-audit first to fix authenticity, then content-review to score readiness.

The two share one banned-hype canon: content-review owns that table as the single source of truth; this skill references it (see taxonomy family 2.1) rather than maintaining a second copy. This skill's authenticity verdict feeds content-review's brand-voice dimension (Dimension 6) — a draft that fails here cannot pass that check.

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Inputs

Input	Required?	Description
The draft	Required	The text to audit. Any length; note if it's an excerpt.
VOICE-PRINT.md	Strongly recommended	Output of voice-print. Gives the rewrite a target instead of a generic one. Without it, rewrites aim at a generic "specific, honest practitioner" voice and the skill says so.
Channel	Optional	Newsletter / LinkedIn / X / blog — calibrates which structural tells matter most (e.g. listicle skeleton is worse in an essay than in a carousel).
Author intent	Optional	What the piece is trying to do. Prevents flagging a deliberate choice as a defect.

BLOCK rule

IF no draft text is provided:
  BLOCK. Return: "Paste the draft you want audited for AI tells. If you have a
  VOICE-PRINT.md, include it — the rewrites will aim at that voice instead of a generic one."

Note on origin: if the user says the text is not AI-written (it's their own), still run the audit — humans absorb these patterns too, especially the hype/transition vocabulary. Frame findings as "reads as AI" not "is AI," and weight the voice print heavily.

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Decision Logic

Step 1 — Scan the six defect families

The full taxonomy — every pattern, why it reads as AI, and the rewrite directive — is in references/ai-tell-taxonomy.md. Read it before auditing. The six families:

#	Family	The tell in one line
1	Structural	Revelation hook ("Here's what no one tells you"), "it's not X, it's Y" reduction, symmetrical listicle skeleton, manufactured stakes
2	Lexical	Hype words (leverage, unlock, seamless, robust), filler ("it's worth noting"), AI-signature words (delve, tapestry, realm, navigate, ever-evolving)
3	Connective	Transition-word scaffolding (moreover, furthermore, additionally, consequently) doing the work real logic should do
4	Rhythm	Uniform sentence length, equal paragraph blocks, relentless parallelism, no fragments, no variance
5	Punctuation/format	The em-dash-as-only-tool tic, bold-everything, emoji bullets, title-case headers, list-for-everything
6	Closing	"In conclusion / Ultimately / At the end of the day," recap-summary, tacked-on uplift or CTA

Step 2 — Score by density, not presence

For each family, assess severity on how pervasive it is, not whether it appears once:

none      — not present, or a single deliberate instance that works
light     — present but occasional; doesn't dominate the read
moderate  — recurring; a reader would start to notice the pattern
heavy     — the pattern is load-bearing; remove it and the structure collapses

Then read co-occurrence: the unmistakable AI signature is several families heavy at once — revelation hook + transition scaffolding + uniform rhythm + em-dash tic + "in conclusion." One family heavy = a tic to fix. Four families heavy = the text has no voice; rewrite, don't patch.

Step 3 — Distinguish tell from legitimate use (the false-positive gate)

Before flagging, apply the gate for that pattern (detailed per-pattern in the taxonomy). The general test:

• Frequency: is it the only tool, or one of several? (Em-dashes once a paragraph = fine.)
• Function: does it carry real meaning, or substitute for it? ("It's not X, it's Y" stating a genuine reframe = fine; doing it three times for rhythm = tell.)
• Voice fit: does the VOICE-PRINT.md record this as a genuine signature move? If the author really does open on a bold claim, that's their voice, not slop.

Flag only what fails the gate. Over-flagging is its own failure — it trains the user to strip out real writing.

Step 4 — Rewrite toward the voice, per defect

For each flagged item, produce a rewrite directive, not just a deletion:

• Quote the offending line.
• Name the family + why it reads as AI.
• Give a specific rewrite that does what the line was trying to do — using the author's voice (from the voice print) and real specificity (a number, a scene, a named thing). If no voice print, aim at the practitioner standard in pmm/DOMAIN.md and say the rewrite is generic.

The reframing principle (cross-ref content-craft): replace the function the slop was faking. A revelation hook fakes "this is worth your attention" — replace it with an actual specific stake. Transition words fake logical connection — replace with the real causal link or cut.

Step 5 — Verdict

The deciding variable between DE-SLOP and REWRITE is does a genuine voice anchor survive? — is there at least one contiguous passage that is really the author, not the machine. Family count alone doesn't decide it.

CLEAN        — no family above light; reads as a real person. Optionally note 1 polish.
DE-SLOP      — tells are present (1–3 families moderate/heavy) AND a voice anchor
               survives. Provide rewrite directives. When slop dominates but one real
               passage holds, the directive is "build outward from the anchor, cut the
               rest" — not patch-in-place.
REWRITE      — heavy tells across many families (typically 4+) AND no passage survives
               the gate; there's no voice anchor anywhere. Recommend: extract the one
               real idea, run voice-print, then redraft. Patching won't save it.

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Outputs

## AI-Slop Audit

**Draft:** [title/desc]   **Channel:** [if given]   **Voice print:** [used / none — rewrites generic]

### Signature read
[1–2 sentences: does this read as AI, and why — name the co-occurring families.]

### Defect scan
| Family | Severity | What's driving it (quoted) |
| Structural | [none/light/moderate/heavy] | "..." |
| ... one row per family |

### Rewrite directives
[Per flagged item:]
**[Family] — "[quoted line]"**
- Why it reads as AI: [one line]
- Rewrite: [specific replacement in the author's voice, with real specificity]

### Verdict: [CLEAN / DE-SLOP / REWRITE]
[Rationale. If REWRITE: point to voice-print + redraft.]

### What's already human
[Lines that work — preserve these. Never omit; de-slopping must protect real voice.]

Feeds: the verdict and brand-voice findings flow into content-review Dimension 6 (Brand voice). A draft that fails ai-slop-audit cannot pass content-review's brand-voice check.

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Cross-Review Triggers

This is itself a review skill; it does not wait on a review of its own. It reads voice-print output and feeds content-review (its authenticity verdict is consumed by content-review's brand-voice dimension — that's the blocking_reviews direction in skill.meta.json: content-review's brand-voice check depends on this, not the reverse). When customer-facing copy is in scope, run ai-slop-audit before content-review so authenticity is fixed before the full GTM scoring.

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Example Usage

Example 1 — Classic AI draft, no voice print

Input: A LinkedIn post opening "Here's the truth no one talks about: AI isn't replacing developers, it's amplifying them. Moreover, the paradigm shift we're seeing is seamless." Output: Signature read = "reads as AI: revelation hook + 'it's not X it's Y' + transition scaffolding + hype all co-occurring." Verdict DE-SLOP with rewrites; flags it has no voice print and recommends one for a sharper rewrite.

Example 2 — Human draft with absorbed tics

Input: A founder's real essay that nonetheless leans on "it's worth noting," "furthermore," and ends "Ultimately, the future is bright." + a VOICE-PRINT.md. Output: CLEAN-leaning-DE-SLOP: structural/rhythm = light (it's genuinely theirs), but connective + closing = moderate. Rewrites the transitions and the ending toward their documented closing instinct (worldview, not uplift). Preserves the rest.

Example 3 — Over-correction guard

Input: A draft with three well-used em-dashes and one rule-of-three that lands. Output: CLEAN. Explicitly does not flag the em-dashes or the triple — they pass the frequency/function gate. Notes that removing them would harm the writing.

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Validation Criteria

Output passes if:

• Severity is scored by density/co-occurrence, not mere presence
• The false-positive gate is applied — deliberate, well-functioning uses are NOT flagged
• Every flagged item has a specific rewrite directive, not just "remove this"
• Rewrites aim at the voice print when present; when absent, the output says rewrites are generic
• A "what's already human" section preserves real voice
• Verdict follows the CLEAN/DE-SLOP/REWRITE logic; REWRITE points back to voice-print
• No recommendation to blanket-ban a punctuation mark or single word

Output fails if:

• It flags every em-dash / every "leverage" mechanically (find-replace behavior)
• Rewrites are generic deletions that leave stiff text
• It treats one instance of a pattern as proof of AI authorship
• It strips a documented signature move because it superficially resembles a tell

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Benchmarks

Authenticity is partly subjective, so this skill is validated primarily by golden example. Two checkable signals do anchor it:

Signal	Target	Source
Banned-hype-pattern conversion penalty	−15 to −30% vs. equivalent clean copy	content-review benchmarks (Nielsen 2025 trust-signal lineage)
False-positive rate on a known-human control passage	0 hard flags on deliberate, well-used patterns	clean-control golden

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References & Sources

Tier-1 / standard:

• Practitioner voice standard — pmm/DOMAIN.md (the rewrite target when no voice print exists)

Tier-2 (operator lineage — adapted, not copied):

• b2b-practitioner-voice (growth-skills v1.0, 9/10) — voice standard
• growth-publish-safety (growth-skills v1.0, 6.5/10) — banned-hype list lineage (shared with content-review)

Cross-references (this repo):

• references/ai-tell-taxonomy.md — the full six-family defect taxonomy + per-pattern gate + rewrite directive
• pmm/voice-print/SKILL.md — produces the rewrite target
• pmm/content-review/SKILL.md — consumes this verdict in its brand-voice dimension; shares the banned-hype list

Output metadata:

---
Skill: ai-slop-audit v1.0.0
Voice print: [used / none]
Verdict: [CLEAN/DE-SLOP/REWRITE]
Generated: [date]
---