Deslopify

Deslopify

Strip the AI fingerprints out of a text and make it good in its genre. The target is prose that reads like one person wrote it for one audience about something they actually know. Detector scores are beside the point; text can score human and still be unreadable.

Why this loops

The "not X but Y" family and its relatives are generative habits. Preference tuning rewards balanced, contrastive, comprehensive-sounding framing, so the contrast move sits deep in the model's priors and surfaces about once a paragraph. Two consequences shape this skill:

1. You cannot see your own slop. The priors that produce the pattern also make it invisible on re-read. So detection runs mechanically, as regex against a fixed catalog. "Does this look AI to me?" is not a detection method.
2. Rewriting reintroduces slop. Ask a model to remove "it's not just X, it's Y" and out comes "this is less about X than Y", the same move in a wig. Every rewrite therefore gets re-scanned, and the loop runs until a scan comes back clean.

Workflow: Scan → Diagnose → Rewrite by meaning → Re-scan → (repeat) → Register check.

Phase 0: Fix the target

Before touching the text, establish:

• Genre and venue. Academic article, tweet, reddit post, LinkedIn, email, blog, docs, marketing. Ask when it isn't stated and isn't obvious from the text. Genre decides which tells are fatal and what "good" means; see references/voices.md.
• Audience and stance. Who reads it, and what the author actually claims. Slop fills the space where a claim should be, so you cannot remove it without knowing the claim.
• Constraints. Length limits, required citations, house style.

Phase 1: Mechanical scan

Run the detection patterns from references/tells.md against the text. If the text is in a file, or you can write it to a temp file, run the grep commands in that reference literally: the catalog is written as runnable grep -Ein patterns. Otherwise apply each pattern by hand, line by line.

Produce a finding list: line or sentence, matched pattern, tell category. Then run the two structural checks regex can't catch:

• Cadence. Flag any run of 3+ consecutive sentences within ±4 words of the same length, and any paragraph where every sentence has the same shape (subject, verb, elaboration).
• Formatting. Bold scattered through prose, emoji-decorated headers or bullets, "Term: definition" bullet lists, headers on a text too short to need them, a tidy intro-three-points-conclusion skeleton.

Report the findings to the user as a short table before rewriting: category, count, worst example. The user should see the diagnosis.

Phase 2: Rewrite by meaning

Go finding by finding. The cardinal rule: never fix a pattern by paraphrasing the pattern. Decide what the sentence asserts, then assert that.

The "not X but Y" family: three-way triage

Every negative parallelism gets exactly one of these treatments:

1. Strawman negation (nobody believes X). Delete the X half and assert Y directly, with whatever evidence the text has.
   • "It's not just a tool, it's a fundamental shift in how teams work" → "Teams that adopted it stopped holding standups within a month."
2. Real contrast (people genuinely hold X). Earn it: name who holds X, say concretely why Y beats it. A real contrast survives being made specific; slop doesn't.
3. Empty claim (the contrast decorates a sentence that asserts nothing). Delete the sentence. Most cases are this one.

Banned escape hatches, all the same move, all counted as new findings: "less about X than Y", "X matters, but Y matters more", "the real X is Y", "the question isn't X, it's Y", "X? Y." (the rhetorical-question variant), and the em-dash form "— not X, but Y".