2nd/10_Wiki/Topics/AI_and_ML/Articulateness.md

---
id: wiki-2026-0508-articulateness
title: Articulateness
category: 10_Wiki/Topics
status: verified
canonical_id: self
aliases: [명료성, articulation, prompt clarity, plain language, technical writing]
duplicate_of: none
source_trust_level: B
confidence_score: 0.85
verification_status: applied
tags: [communication, writing, prompt-engineering, technical-writing, plain-language, llm-collab]
raw_sources: []
last_reinforced: 2026-05-10
github_commit: pending
tech_stack:
  language: writing / communication
  applicable_to: [Prompt Engineering, Documentation, PR Description, Spec Writing]
---

# Articulateness

## 📌 한 줄 통찰
> **"매 thought 의 high-resolution output"**. 매 head 의 fuzzy idea 의 매 lossless 의 transmit. 매 AI 시대 의 가장 큰 leverage — 매 prompt 의 articulate = 매 output 의 quality. 매 vocabulary 의 X, 매 clarity 의 win.

## 📖 핵심

### 매 components
1. **Vocabulary precision**: 매 정확 단어 선택. 매 vague vs specific.
2. **Structural clarity**: 매 conclusion-first (BLUF, Bottom Line Up Front).
3. **Nuance**: 매 audience 의 calibrate.
4. **Cohesion**: 매 logical flow 의 transition.
5. **Concision**: 매 superfluous word 의 cut.

### 매 BLUF (Bottom Line Up Front)
- ❌ "Background, then build-up, then conclusion."
- ✅ "Conclusion. Then evidence."

→ 매 reader 의 시간 존중.

### Plain Language (매 modern standard)
- 매 short sentence (15-20 word).
- 매 active voice ("X did Y" > "Y was done by X").
- 매 concrete > abstract.
- 매 jargon 의 explain.
- 매 multinational 의 translation 의 friendly.

→ US Plain Writing Act (2010), GOV.UK style guide.

### 매 prompt engineering 의 articulateness
1. **Specific**: 매 "write a poem" → "매 4-line haiku 의 autumn".
2. **Constraint**: 매 length, 매 style, 매 audience.
3. **Example**: 매 few-shot.
4. **Role**: 매 "act as senior backend engineer".
5. **Output format**: 매 JSON, 매 bullet, 매 markdown.

### 매 technical writing 의 hierarchy
1. **README**: 매 30-second pitch.
2. **Tutorial**: 매 narrative, hand-holding.
3. **How-to**: 매 task-oriented.
4. **Reference**: 매 exhaustive.
5. **Explanation**: 매 conceptual.

→ Diátaxis framework.

### Anti-clarity 의 source
- 매 jargon 의 over-use.
- 매 passive voice.
- 매 nominalization ("perform an analysis" > "analyze").
- 매 abstract noun ("optimization", "leverage").
- 매 throat-clearing ("It is important to note that...").

## 💻 패턴

### Prompt template (specific + constraint)
```
Role: Senior TypeScript backend engineer.
Task: Refactor this function for testability.
Constraints:
- Keep the public signature unchanged.
- Extract DB call to a repository interface.
- Return a Result<T, E> instead of throwing.
- Output: code only, no explanation.

Input:
{{code}}
```

→ 매 vague "make it better" 의 X.

### PR description template
```markdown
## Why
[1-2 sentence motivation]

## What changed
- bullet
- bullet

## How to verify
- [ ] step 1
- [ ] step 2

## Risk
[regression area / rollback plan]

## Out of scope
[what NOT done — prevent reviewer churn]
```

### Plain language rewrite
```
❌ Original (50 words):
"It is recommended that users should consider implementing
appropriate validation mechanisms in order to ensure that 
input data is properly sanitized before being processed."

✅ Rewrite (10 words):
"Validate input before processing."
```

### Articulateness 의 self-check
```
1. 매 첫 sentence 의 conclusion?
2. 매 sentence avg < 25 word?
3. 매 active voice 의 80%+?
4. 매 jargon 의 explain or replace?
5. 매 reader 의 next step 의 clear?
```

## 🤔 결정 기준
| 상황 | 우선 |
|---|---|
| Spec / RFC | Structural clarity + precision |
| README | BLUF + plain language |
| PR description | Why + what + risk |
| LLM prompt | Specific + constraint + format |
| Slack / async | Concise + actionable |
| Customer-facing | Plain + nuance |

**기본값**: BLUF + active + concise + concrete.

## 🔗 Graph
- 변형: [[Plain-Language]] · [[Technical-Writing]]
- 응용: [[Prompt_Engineering|Prompt-Engineering]] · [[PR-Template]]
- Adjacent: [[Vocabulary-Expansion]]

## 🤖 LLM 활용
**언제**: 매 prompt 의 craft. 매 doc / spec / PR write. 매 communication 의 review.
**언제 X**: 매 creative writing 의 nuance 의 sacrifice. 매 poetic context.

## ❌ 안티패턴
- **Throat-clearing**: 매 "It is important to note that..."
- **Passive voice abuse**: 매 actor 의 hide.
- **Jargon dump**: 매 audience 의 ignore.
- **Burying lede**: 매 conclusion 의 끝.
- **Nominalization**: "perform an analysis" 의 "analyze".
- **Vague prompt**: 매 "make it better" 의 LLM 에 unhelpful.

## 🧪 검증 / 중복
- Verified (Plain Writing Act, GOV.UK style, Diátaxis).
- 신뢰도 B.
- Related: [[Prompt_Engineering|Prompt-Engineering]] · [[Technical-Writing]] · [[Plain-Language]].

## 🕓 Changelog
| 날짜 | 변경 |
|---|---|
| 2026-05-08 | Phase 1 |
| 2026-05-10 | Manual cleanup — BLUF + Plain Language + Diátaxis + prompt template |