// [Document Processing] Use when you need to convert markdown files to PDF with syntax highlighting and custom CSS support.
[HINT] Download the complete skill directory including SKILL.md and all related files
| name | markdown-to-pdf |
| version | 1.0.0 |
| description | [Document Processing] Use when you need to convert markdown files to PDF with syntax highlighting and custom CSS support. |
| disable-model-invocation | true |
Goal: Convert Markdown files to PDF with syntax highlighting and custom CSS support.
Workflow:
Key Rules:
Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).
Convert markdown files to high-quality PDF documents with code syntax highlighting and custom CSS support.
This skill requires npm dependencies. Run one of the following:
# Option 1: Install via ClaudeKit CLI (recommended)
ck init # Runs install.sh which handles all skills
# Option 2: Manual installation
cd .claude/skills/markdown-to-pdf
npm install
Dependencies: md-to-pdf, gray-matter
Note: First run may download Chromium (~150MB) unless system Chrome is detected.
# Basic conversion
node .claude/skills/markdown-to-pdf/scripts/convert.cjs --input ./README.md
# Specify output path
node .claude/skills/markdown-to-pdf/scripts/convert.cjs --input ./doc.md --output ./output.pdf
# With custom CSS
node .claude/skills/markdown-to-pdf/scripts/convert.cjs --input ./doc.md --css ./my-style.css
| Option | Short | Description | Default |
|---|---|---|---|
--input | -i | Input markdown file path | (required) |
--output | -o | Output PDF file path | {input}.pdf |
--css | -c | Custom CSS file path | built-in |
--no-highlight | Disable syntax highlighting | false | |
--help | -h | Show help message |
The default PDF style includes:
Returns JSON on success:
{
"success": true,
"input": "/path/to/input.md",
"output": "/path/to/output.pdf",
"pages": 3
}
Chrome not found: The skill will automatically download Chromium. Set PUPPETEER_SKIP_DOWNLOAD=1 to prevent this.
Memory issues: Large documents may require more memory. Consider splitting into multiple files.
Font issues: Embed fonts via CSS @font-face with base64-encoded fonts for consistent rendering.
[IMPORTANT] Use
TaskCreateto break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.
AI Mistake Prevention — Failure modes to avoid on every task: Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal. Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing. Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain. Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path. When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site. Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code. Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks. Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis. Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly. Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.
Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.
MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.
MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.
IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting
IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code
IMPORTANT MUST ATTENTION cite file:line evidence for every claim (confidence >80% to act)
IMPORTANT MUST ATTENTION add a final review todo task to verify work quality
[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using TaskCreate.