Agent skill · writing content · sickn33
mdpr-skill
Review MDPR Markdown presentation workflows with semantic hints, visual checks, and deterministic renderer boundaries.
Why this skill is useful
Provides specific workflows and semantic review processes for MDPR that the AI wouldn't generate on its own.
What it needs
About 5k tokens when loaded. Last updated 2026-08-07. 44,571 stars on the source repository.
What this skill does
mdpr-skill Overview Use this skill as the optional agent companion for MDPR, a deterministic Markdown-to-presentation runtime. MDPR owns parsing, layout, theming, validation, and final PPTX/HTML/PDF rendering. This skill helps an agent review MDPR workflows, propose weak semantic hints, and explain visual findings without taking control of slide geometry. The upstream skill source is ch040602/mdpr-skill, which includes schemas, review commands, compatibility artifacts, visual evidence examples, and MDPR boundary documentation. When to Use This Skill Use when the user asks about MDPR, mdpresent, Markdown-to-PPTX, or Markdown presentation review. Use when generated MDPR artifacts need semantic, narrative, accessibility, or visual review notes. Use when the user wants Codex-style presentation workflow hints while keeping MDPR as the deterministic renderer. Use when comparing MDPR output against image-only deck generators such as a codex-ppt style workflow. Use when a reusable theme or style-pack proposal should be expressed as an approval-bound MDPR candidate instead of direct final slide edits. Core Boundary Let MDPR own parsing, slide splitting, recipes, layout, coordinates, geometry, typography, colors, z-order, arrows, effects, exact icon assets, renderer object IDs, and final PPTX objects. Keep agent output semantic, evidence-based, and schema-valid. Express fixes as Markdown cleanup, MDPR rulebook changes, config changes, deterministic policy changes, or approval-bound proposals. Preserve the ability to build the same deck with all agent hints disabled. Do not mutate source Markdown unless the user explicitly asks for a cleaned source draft. How It Works Step 1: Identify the MDPR Surface Classify the user's request before producing advice: semantic hints: compact intent, grouping, importance, and icon-keyword suggestions. review report: visual or narrative concerns grounded in rendered evidence, manifests, or validation reports. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills sickn33/mdpr-skill--d44bb7