Technical Copywriting Review

SkillDev tools

Use when reviewing teaser/promotion text for sharing technical blog posts. Triggers include "티저 리뷰", "포스트 공유", "copywriting review", "teaser review", "promotion text", "LinkedIn post review"

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Technical Copywriting Review skill

What this skill tells your AI

The instructions your AI receives, as published by toongri/oh-my-toong-playground in skills/technical-copywriting/SKILL.md and read by ahel’s review.

Reviews teaser/promotion text that accompanies technical blog post shares. 3-phase sequential review: Type Classification → Structure Review → Voice & Authenticity.

The Iron Law

  • Perform all 3 Review Areas in order. Do not skip any Area.
  • After completing each Area, present review results to the user and get approval.
  • All principles are recommendations. Apply flexibly based on context.

Non-Negotiable Rules

RuleDescription
Sequential ExecutionType → Structure → Voice order
Per-Area ApprovalUser confirmation after each Area
Before/AfterAll improvement suggestions in Before/After format
Cite PrincipleEach suggestion must cite its principle ID (CP1~CP15)

Review Areas

digraph review_flow {
    rankdir=LR;
    node [shape=box];

    "Input Text" -> "Area 1:\nType Classification";
    "Area 1:\nType Classification" -> "Area 2:\nStructure Review";
    "Area 2:\nStructure Review" -> "Area 3:\nVoice & Authenticity";
    "Area 3:\nVoice & Authenticity" -> "Review Complete";
}

Area 1: Type Classification

  • Reviews: Teaser type classification, required elements verification per type, platform constraint compliance
  • Enter when: Review target text exists
  • Skip when: User already specified type and requested no type verification
  • Reference: references/type.md

Area 2: Structure Review

  • Reviews: Type-specific opening, value delivery mode, closing pattern, proportion balance
  • Enter when: Area 1 completed
  • Skip when: Only voice-level review requested
  • Reference: references/structure.md

Area 3: Voice & Authenticity Review

  • Reviews: Developer authenticity, anti-marketing-speak, platform tone, reader connection, Korean naturalness
  • Enter when: Area 2 completed (or Area 1 if Area 2 skipped)
  • Skip when: Only structure-level review requested
  • Reference: references/voice.md

Review Output Format

Each Area's review results use this format:

## Area N: {Area Name} Review

### Summary
- 총 {N}건의 개선 제안
- 심각도: Critical {N} / Suggestion {N}

### Findings

#### Finding 1: {Title}
- **원칙**: {Principle ID} - {Principle name}
- **심각도**: Critical / Suggestion
- **Before**:
  > {Original text}
- **After**:
  > {Improved text}
- **근거**: {Why this change is needed}

Severity criteria:

  • Critical: Type mismatch (e.g. Learning Journey structure applied to Announcement), missing required elements for the identified type, platform constraint violations
  • Suggestion: Tone adjustment, proportion optimization, minor structural improvement

Area Completion Protocol

After completing each Area:

  1. Present review results in Review Output Format
  2. Ask user: "Area N 리뷰 결과를 확인해주세요. 다음 Area로 진행할까요?"
  3. Proceed to next Area after user approval

Review Completion

After all 3 Areas are complete:

  1. Present overall review summary (finding count per Area, Critical/Suggestion ratio)
  2. Priority-ordered improvement list (Critical → Suggestion)
  3. Generate improved full teaser text upon user request

Language

  • Review results are written in Korean
  • Principle IDs remain in English codes (CP1, CP2, etc.)
  • Before/After examples maintain the original language

Signals

GitHub stars
25
Forks
1
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
technical-copywriting
Source
github.com/toongri/oh-my-toong-playground