pdf-to-markdown

name	pdf-to-markdown
version	1.0.0
description	[Document Processing] Use when you need to convert PDF files to Markdown with support for native text PDFs and scanned documents (OCR).
disable-model-invocation	false

Quick Summary

Goal: Convert PDF files to well-formatted Markdown with auto-detection of native text vs scanned documents.

Workflow:

1. Auto-Detect — Determine if PDF has native text or needs OCR
2. Convert — Run scripts/convert.cjs with input path and optional mode/output flags
3. Output — Returns JSON with success status, page count, and output path

Key Rules:

• Use --mode auto (default) to let the tool decide native vs OCR
• OCR for scanned PDFs requires additional tesseract.js setup
• Complex multi-column layouts may not preserve structure perfectly

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

pdf-to-markdown

Convert PDF files to Markdown format with automatic detection of native text vs scanned documents.

Installation Required

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/pdf-to-markdown
npm install

Dependencies: @opendocsg/pdf2md (native PDFs), pdfjs-dist (PDF parsing)

Note: OCR for scanned PDFs requires additional setup (see OCR section).

Quick Start

# Basic conversion (auto-detect native vs scanned)
node .claude/skills/pdf-to-markdown/scripts/convert.cjs --input ./document.pdf

# Specify output path
node .claude/skills/pdf-to-markdown/scripts/convert.cjs -i ./doc.pdf -o ./output.md

# Force native mode (skip OCR detection)
node .claude/skills/pdf-to-markdown/scripts/convert.cjs -i ./doc.pdf --mode native

CLI Options

Option	Short	Description	Default
--input	-i	Input PDF file path	(required)
--output	-o	Output markdown file path	{input}.md
--mode	-m	Conversion mode: auto, native, ocr	auto
--help	-h	Show help message

Features

• Auto-Detection: Automatically determines if PDF has native text or requires OCR
• Native PDFs: Fast extraction using @opendocsg/pdf2md
• Tables: Basic table structure preservation
• Cross-OS: Works on Windows, macOS, Linux
• No System Dependencies: Pure JavaScript implementation

Conversion Modes

Auto (Default)

Checks if PDF has extractable text on first page. Uses native extraction if text found, otherwise falls back to OCR warning.

Native

Fast direct text extraction. Best for PDFs with selectable text (not scanned images).

OCR (Scanned PDFs) - Coming Soon

For scanned documents. Currently not implemented - the skill will notify you if a PDF appears to be scanned.

Output

Returns JSON on success:

{
    "success": true,
    "input": "/path/to/input.pdf",
    "output": "/path/to/output.md",
    "stats": {
        "pages": 5,
        "mode": "native"
    }
}

Limitations

• Complex multi-column layouts may not preserve structure
• Scanned PDF OCR accuracy depends on image quality
• Mathematical formulas may not convert perfectly
• First-run OCR downloads language data (~15MB)

OCR Setup (Optional)

For scanned PDF support, install additional dependencies:

npm install tesseract.js pdfjs-dist canvas

Note: The canvas package may require build tools on some systems.

---

[IMPORTANT] Use TaskCreate to 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:

Re-read files after context changes. Context compaction, resume, or long-running work can make memory stale; verify current files before acting. Verify generated content against source evidence. AI hallucinates APIs, names, claims, and document facts. Check the relevant source before documenting or referencing. Check downstream references before deleting or renaming. Removing an artifact can stale docs, generated mirrors, configs, and callers; map references first. Trace the full impact chain after edits. Changing a definition can miss derived outputs and consumers. Follow the affected chain before declaring done. Verify ALL affected outputs, not just the first. One green check is not all green checks; validate every output surface the change can affect. Assume existing values are intentional — ask WHY before changing. Before changing a constant, limit, flag, wording, or pattern, read nearby context and history. Surface ambiguity before acting — don't pick silently. Multiple valid interpretations require an explicit question or stated assumption with risk. Keep shared guidance role-relevant. Universal guidance must help every receiving skill or agent; code-specific obligations belong only in code-specific protocols.

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 + sequential thinking — every claim needs appropriate traced evidence (file:line for repo/code claims; source URL or artifact section for research, product, content, and docs claims); confidence >80% to act, <60% DO NOT recommend. Anti-hallucination: never present guess as fact, admit uncertainty freely, cross-reference independently, stay skeptical of own confidence.

MUST ATTENTION apply AI mistake prevention — verify generated content against evidence, trace downstream references before deleting or renaming, verify all affected outputs, re-read files after context loss, and surface ambiguity before acting.

Closing Reminders

IMPORTANT MUST ATTENTION Goal: Convert PDF files to well-formatted Markdown with auto-detection of native text vs scanned documents.

Protocols in force (concise digest of the SYNC/shared blocks this skill carries):

• AI Mistake Prevention: verify generated content against evidence, trace downstream references, verify all affected outputs, re-read after context loss, surface ambiguity.
• Critical Thinking: Sequential thinking, traced file:line proof, confidence >80% to act.

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.