anti-ai-writing

这段内容是审核时保存的快照。外部来源才是完整且最新的版本。

---
name: anti-ai-writing
description: Use when writing or auditing any written content — captions, carousels, newsletters, threads, LinkedIn posts, long-form — and as the FINAL filter on every piece. Reach for it whenever text feels generic, fluent-but-hollow, over-formatted, or "sounds like AI." Strongest on written prose; lighter on spoken reels.
---

# Anti-AI Writing

**The goal is not "don't sound like AI."** That framing loses — blocklists rot, and chasing a negative gives you a beige voice. The goal is: **sound like a specific person who has thought about the thing and has something to say.** Specificity is the moat. Voice is the moat. Everything below serves those two.

Apply with judgment. **Spirit beats letter.** If a rule makes the sentence worse, break it.

## Where this runs

This skill matters most on **written content** — text a reader's eye scans. Run the **full pass** there: captions, carousels, newsletters, threads, LinkedIn, long-form, DMs, landing copy. It's the last filter on every written piece.

On **spoken content** (reel and video scripts — the words get said aloud), run the **spoken subset only**:
- **Apply:** specificity (Level 3+), kill hollow reframes that don't pay off, cut borrowed-authority / thinkfluencer filler, cut significance inflation. These hurt out loud too.
- **Skip:** the formatting tells (em dashes, bullets, hashtags don't exist in speech), and go light on the vocab blocklist — spoken cadence forgives, and your voice plus the **viral-hooks** and **storytelling** skills are already doing the heavy de-AI-ing. Over-applying prose rules to a script makes it sound stilted, not human.

**The split can live inside a single piece.** When you produce a reel, the *script* is spoken (subset), but the *caption* that ships with it is written (full pass). Apply the right intensity to each part of the output, not one blanket pass.

## The 5 diseases (diagnose before you fix)

Most AI writing fails for one of five reasons. Name the disease and the fix is obvious. If you can't name it, **read the line aloud** — the disease becomes audible.

1. **Vagueness compression** — describes a category, not a thing. *"Users were frustrated"* → "users clicked export six times because nothing loaded."
2. **Significance inflation** — treats normal facts like turning points. *"This marks a pivotal shift in onboarding"* → state the fact, let the reader weigh it.
3. **Hedged confidence** — has a position but won't commit. *"It could be argued that…"* → take the position or cut the sentence.
4. **Rhythmic flatness** — every sentence the same length, every paragraph three sentences. → break the meter.
5. **Borrowed authority** — sounds like a McKinsey deck or a LinkedIn thinkfluencer. No fingerprint. → write it the way you'd say it to one person.

## Rule priority (when rules collide)

**Accurate > Clear > Specific > Voiced > Stylish.** Never sacrifice accuracy for style. A boring true sentence beats an elegant vague one.

## Specificity — the whole game

The single highest-leverage rule. Specific beats polished, every time. The ladder:

| Level | Example |
|---|---|
| Vague | "The company faced challenges." |
| Specific | "The company had cashflow issues." |
| Concrete | "The company missed payroll twice in six months." |
| Lived | "Payroll bounced in March and again in August. The CFO found out from Slack." |

Aim for **level 3 minimum**, level 4 if you have it. Replace categories with instances, adjectives with numbers, "users" with "the kind of user who [does specific thing]." If you don't have the specific, get it before writing — or admit it plainly ("I don't know the exact number, but it felt like roughly half"). Pull real specifics from your own notes and lived experience; never invent numbers or events.

## The negative parallelism ban (the #1 tell)

The biggest single tell of AI writing. The pattern:

> "It's not X. It's Y."

…and every variation that knocks down a frame to sound insightful: *Not X. Y. / Less