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Mck-ppt-design-skill

Consulting firm-style PowerPoint design system for AI agents. 70 layout patterns, flat design, python-pptx. 麦麸风格PPT设计系统。

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MCK PPT Design Skill

AI-native PowerPoint design system — 67 layouts · Harness Engineering · BLOCK_ARC charts · QA pipeline · Python runtime

Copyright © 2024-2026 Kaku Li. Licensed under Apache 2.0. See NOTICE for details.

English · 中文说明 · Harness Guide


🖼️ Sample Output

Cover PageStrategy AnalysisData Dashboard
4-Column FrameworkColor SystemExecutive Summary

⚡ Quick Start

pip install python-pptx lxml
import sys, os
sys.path.insert(0, os.path.expanduser('~/.workbuddy/skills/mck-ppt-design'))
from mck_ppt import MckEngine
from mck_ppt.constants import *

eng = MckEngine(total_slides=12)
eng.cover(title='Q1 2026 Strategy Review', subtitle='Board Presentation', date='2026')
eng.toc(items=[('1', 'Market Overview', 'Current landscape'), ('2', 'Strategy', 'Key actions')])
eng.table_insight(title='Three shifts driving market restructuring',
    headers=['Dimension', 'Before', 'After'],
    rows=[['Distribution', 'Offline-first', 'Digital-first'],
          ['Pricing', 'Cost-plus', 'Value-based']],
    insights=['Digital channels now control 60% of CAC', 'Value pricing unlocks 3× margins'])
eng.donut(title='Revenue Mix', segments=[(0.45, NAVY, 'Product'), (0.35, ACCENT_BLUE, 'Service'), (0.20, ACCENT_GREEN, 'Other')])
eng.timeline(title='12-month roadmap', milestones=[('Q1', 'Foundation'), ('Q2', 'Pilot'), ('Q3', 'Scale'), ('Q4', 'Review')])
eng.closing(title='Thank You')
eng.save('output/deck.pptx')

AI Agent Compatibility

AI AgentStatus
WorkBuddy / Codebuddy✅ Native skill (mck-ppt-design)
Claude / Claude Code✅ Load SKILL.md as skill
Cursor / Continue✅ Add as project rule
Any LLM✅ Feed SKILL.md as context

🔱 Harness Engineering Mode

New in v2.3.3-harness — Transforms the skill from vibe-coding into structured 5-stage generation with machine-readable gates.

The Problem: Vibe Coding vs. Harness

Without Harness, the entire 3,967-line SKILL.md was loaded every time, AI jumped straight to code, and errors were only discovered after rendering. With Harness, context is loaded progressively, structure is locked before content, and gates run as Python scripts — not AI self-evaluation.


GitHub에서 전체 내용 보기