# Anti AI Writing

> Universal anti-AI slop filter applied to ALL written output. Bans AI-overused words, enforces human tone, prevents generic marketing-blog copy. Use when generating any text content — docs, scripts, emails, PRDs, reports, commit messages, or any prose. Always active as a quality gate on written output.

- Skill: `kmshihab7878/anti-ai-writing` (Agent Skill)
- Install (CLI): `npx skillmds@latest add kmshihab7878/anti-ai-writing`
- Raw SKILL.md: https://api.skillmd.com/api/skills/kmshihab7878/anti-ai-writing/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Marketing & Growth
- Author: kmshihab7878 (https://skillmd.com/u/kmshihab7878)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/kmshihab7878/anti-ai-writing

---


# Anti-AI Writing

Enforce human, concrete, evidence-backed writing across all departments. This skill is the universal anti-slop layer — the difference between generic AI output and content that sounds like it was written by someone who knows what they're talking about.

## When to use

Apply these rules to ALL written output:
- Documentation, READMEs, architecture docs
- PRDs, user stories, specs
- Ad scripts, marketing copy, emails
- Commit messages, PR descriptions
- Reports, analyses, briefs
- Slack messages, comments
- Any prose generated by any agent

## When NOT to use

- Code (variable names, comments in code follow coding-workflow rules)
- Raw data output (JSON, CSV, logs)
- Verbatim quotes from external sources

## Banned Words and Phrases

### Tier 1: Hard Ban (never use)

These words appear in >90% of AI-generated text and <5% of human writing. Using them instantly flags output as AI-generated.

| Banned | Use Instead |
|--------|-------------|
| delve | dig into, explore, examine |
| tapestry | mix, combination, set |
| landscape | market, space, field |
| realm | area, field, domain |
| multifaceted | complex, varied |
| holistic | complete, full, whole |
| synergy / synergize | combined effect, work together |
| leverage (as verb) | use, apply, build on |
| utilize | use |
| facilitate | help, enable, run |
| endeavor | try, attempt, effort |
| commendable | good, strong, impressive |
| testament | proof, evidence, sign |
| pivotal | key, critical, important |
| paramount | essential, critical, top |
| foster | build, encourage, grow |
| comprehensive | full, complete, thorough |
| intricate | complex, detailed |
| nuance / nuanced | subtle, specific, detailed |
| underscore | highlight, show, prove |
| innovative | new, novel, original |
| streamline | simplify, speed up, cut |
| robust | strong, reliable, solid |
| seamless | smooth, easy, invisible |
| cutting-edge | latest, newest, modern |
| groundbreaking | new, first, original |
| transformative | major, significant |
| game-changer | breakthrough, shift |
| paradigm shift | change, shift |
| deep dive | analysis, review, look |
| at the end of the day | ultimately, in practice |
| it's important to note that | [delete — just state the thing] |
| in today's fast-paced world | [delete entirely] |
| look no further | [delete entirely] |
| it's worth noting | [delete — just state it] |
| navigate (metaphorical) | handle, manage, deal with |
| a]myriad of | many, several, various |
| plethora | many, lots of |

### Tier 2: Restricted (use sparingly, max 1 per document)

| Restricted | When Acceptable |
|------------|----------------|
| ecosystem | Only when referring to actual software/platform ecosystems |
| empower | Only when describing literal capability grants (permissions, access) |
| harness | Only when referring to actual tools/systems being connected |
| spearhead | Only when attributing a specific person leading a specific initiative |
| optimize | Only in technical/mathematical contexts (query optimization, compiler optimization) |

### Tier 3: Pattern Bans

| Pattern | Problem | Fix |
|---------|---------|-----|
| "In conclusion..." | AI summary tic | End with the last point, or say "Bottom line:" |
| Starting with "Certainly!" or "Absolutely!" | Sycophantic filler | Start with the answer |
| "Great question!" | Patronizing | Answer the question |
| Three adjectives in a row | AI padding | Pick the one that matters most |
| "This ensures that..." | Vague causation | State what specifically happens and why |
| Ending with "...and beyond" | Lazy trailing | Be specific about scope |
| "Whether you're a... or a..." | Fake inclusivity | Name your actual audience |

## Structural Rules

### Sentence Level
- **Lead with the point.** Don't build up to it.
- **One idea per sentence.** If a sentence has "and" + "which" + "that", split it.
- **Short > long.** If you can say it in 8 words, don't use 20.
- **Active voice.** "We shipped the feature" not "The feature was shipped by the team."
- **Concrete > abstract.** "Reduced API latency from 400ms to 50ms" not "Significantly improved performance."

### Paragraph Level
- **Max 3 sentences per paragraph** in docs and emails.
- **No wall-of-text paragraphs.** If it's more than 4 lines, break it up or use bullets.
- **First sentence = topic sentence.** Reader should know what the paragraph is about from line 1.

### Document Level
- **No throat-clearing intros.** Don't start with "In the ever-evolving world of..." — start with what matters.
- **Evidence for every claim.** "Performance improved" → "p95 latency dropped from 400ms to 50ms (PR #247)."
- **Numbers over adjectives.** "Fast" → "50ms." "Many" → "147." "Recently" → "March 18."
- **Name things.** "The tool" → "Ruff." "The framework" → "FastAPI." "The database" → "PostgreSQL."

## Voice Calibration

Before writing, load the department-specific voice file from `~/.claude/contexts/{department}/voice.md`. If no department file exists, default to:

- **Tone:** Direct, confident, specific
- **Register:** Professional but not corporate
- **Personality:** Someone who's done this before and is sharing what works
- **Humor:** Dry wit acceptable, never forced
- **Hedging:** Minimize ("I think", "perhaps", "it might be") — either state it or flag uncertainty explicitly

## Self-Check (Run Before Output)

Before finalizing any written output, scan for:

1. **Banned word check** — grep output against Tier 1 list. Replace all hits.
2. **Adjective density** — if >3 adjectives in any sentence, cut to 1-2.
3. **Evidence check** — any claim without a number, name, or citation? Add one or soften to opinion.
4. **Opening check** — does the first sentence start with a banned pattern? Rewrite.
5. **Length check** — any paragraph >4 lines? Break it up.

## Integration with UAOP

This skill is Stage 2 (Context Training) in the Universal Autonomous Operating Pattern. Every department's pipeline loads this skill PLUS their department-specific context files before generating any output.

```
Load order:
1. anti-ai-writing/SKILL.md (this file — universal rules)
2. contexts/{department}/rules.md (department-specific constraints)
3. contexts/{department}/voice.md (department tone)
4. contexts/{department}/domain.md (department knowledge)
5. contexts/{department}/audience.md (who consumes the output)
```