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Z Smart Xparse

Community
tjxj
z-smart-xparse

Parse documents into clean markdown or structured JSON via xparse-cli, with smart PDF auto-split and merge. Use this skill when the user provides a PDF, image, Office file, HTML, OFD, or other supported document and wants it read, converted, summarized, or prepared for downstream agent use. For PDF files, automatically detects files larger than 5 MB or documents longer than 100 pages and splits them into manageable chunks, parses each chunk, then merges results into a single coherent output. Handles encrypted PDFs, page ranges, markdown/text output, and detailed structured extraction.

Overview

Publishertjxj
Repositoryz-skills
Skill namez-smart-xparse
Stars
548
Forks
102
Bundled files
4
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by tjxj on GitHub. Read the source before you install it.

Installation

Install the Z Smart Xparse AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/tjxj/z-skills/tree/main/z-smart-xparse
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/tjxj/z-skills.git /tmp/z-skills
mkdir -p .claude/skills
cp -r /tmp/z-skills/z-smart-xparse .claude/skills/z-smart-xparse
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Z Smart Xparse in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Z Smart Xparse on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Z Smart Xparse is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

z-smart-xparse

Overview

An enhanced document parsing skill with smart PDF auto-split and merge. For non-PDF files, behaves identically to the standard xparse-parse skill. For PDF files, automatically checks file size and page count before parsing — large or long PDFs are split into chunks, parsed individually, then merged into a single result.

Compatibility

Requires the xparse-cli binary. Free API supports PDF and images with zero config; paid API unlocks additional formats (Doc(x)/Ppt(x)/Xls(x)/HTML/OFD/RTF, etc.) and requires paid credentials configured via xparse-cli auth (recommended), or XPARSE_APP_ID/XPARSE_SECRET_CODE env vars. For PDF splitting, requires qpdf or Python 3 with pypdf installed.

Use the parse CLI first. Read the result before requesting any more detail.

Routing Rules

  • For local document tasks, try z-smart-xparse before Python, PDF libraries, OCR tools, or custom scripts.
  • Do not start with Python, PyMuPDF, PyPDF, qpdf, OCR MCP, or image conversion unless z-smart-xparse has already failed or the task clearly exceeds its scope.
  • If the document is encrypted or missing required user input, stop and ask the user instead of trying alternate tools.
  • If the default parse result is sufficient, stop. Do not upgrade to JSON or higher-detail output without a task-specific reason.
  • Only fall back to OCR, image analysis, or custom scripting after you have clearly determined that z-smart-xparse cannot complete the requested task by itself.

Setup

xparse-cli

Check if installed: xparse-cli version

If command not found after install, try the absolute path: ~/.local/bin/xparse-cli version

Update to latest version: xparse-cli update

If available, skip to Quick start below. If not found, install:

PlatformCommand
Linux / macOSsource <(curl -fsSL https://dllf.intsig.net/download/2026/Solution/xparse-cli/install.sh)
Windows (PowerShell)irm https://dllf.intsig.net/download/2026/Solution/xparse-cli/install.ps1 | iex

PDF Splitting Dependencies (only needed for large PDFs)

Check if qpdf is installed: qpdf --version

If not found, install:

PlatformCommand
macOSbrew install qpdf
Linuxsudo apt install qpdf or sudo yum install qpdf

Alternatively, Python 3 with pypdf works: pip install pypdf

Quick Start

Zero config — free API, no registration needed. Supports PDF and images only.

bash
# Non-PDF or small PDF: parse directly
xparse-cli parse report.pdf                         # Markdown → stdout

# Large PDF: skill auto-detects and handles splitting (see Smart PDF Parsing below)

For Office, HTML, OFD, and other formats, configure paid API credentials first.

Smart PDF Parsing (Auto-Split & Merge)

This is the core enhancement over the standard xparse-parse skill. Only applies to PDF files. All other file types skip directly to Step 5.

Step 1: Detect — Check File Size and Page Count

bash
# Get file size in bytes
FILE_SIZE=$(stat -f%z "input.pdf" 2>/dev/null || stat -c%s "input.pdf" 2>/dev/null)

# Get page count using qpdf
PAGE_COUNT=$(qpdf --show-npages "input.pdf" 2>/dev/null)

# Fallback: use Python if qpdf is unavailable
PAGE_COUNT=$(python3 -c "from pypdf import PdfReader; print(len(PdfReader('input.pdf').pages))" 2>/dev/null)

Step 2: Decide — Determine if Splitting is Needed

NEED_SPLIT = false
CHUNK_SIZE = 50   # pages per chunk (safe for free API limit of 50 pages/request)

IF file_size > 5242880 (5 MB):
    NEED_SPLIT = true

IF page_count > 100:
    NEED_SPLIT = true

IF page_count is unknown AND file_size > 5242880:
    NEED_SPLIT = true

Thresholds:

ConditionAction
≤ 5 MB AND ≤ 100 pagesParse directly with xparse-cli parse (no splitting)
> 5 MB OR > 100 pagesSplit into chunks, parse each, then merge

Chunk sizing:

  • Default: 50 pages per chunk (safe for both free and paid API)
  • If paid API is configured: can increase to 200 pages per chunk for efficiency
  • If file is > 5 MB but ≤ 100 pages: split by file size (~4MB per chunk) using page estimation

Step 3: Split — Extract PDF Chunks

Option A: Using qpdf (preferred)

bash
# Create temp directory for chunks
mkdir -p /tmp/xparse-chunks

# Split into chunks of CHUNK_SIZE pages
# Example: 150-page PDF with CHUNK_SIZE=50 → 3 chunks
qpdf input.pdf --pages . 1-50   -- /tmp/xparse-chunks/chunk_001.pdf
qpdf input.pdf --pages . 51-100 -- /tmp/xparse-chunks/chunk_002.pdf
qpdf input.pdf --pages . 101-150 -- /tmp/xparse-chunks/chunk_003.pdf

Option B: Using Python pypdf

python
from pypdf import PdfReader, PdfWriter
import math, os

reader = PdfReader("input.pdf")
chunk_size = 50
total = len(reader.pages)
out_dir = "/tmp/xparse-chunks"
os.makedirs(out_dir, exist_ok=True)

for i in range(0, total, chunk_size):
    writer = PdfWriter()
    for page in reader.pages[i:i+chunk_size]:
        writer.add_page(page)
    chunk_path = os.path.join(out_dir, f"chunk_{i//chunk_size+1:03d}.pdf")
    with open(chunk_path, "wb") as f:
        writer.write(f)

For size-based splitting (>5 MB but ≤100 pages):

Estimate pages per chunk: pages_per_chunk = floor(total_pages * 4MB / file_size_MB)

Then split using the same methods above.

Step 4: Parse & Merge

Parse each chunk sequentially:

bash
# Parse chunk 1 → save markdown
xparse-cli parse /tmp/xparse-chunks/chunk_001.pdf --output /tmp/xparse-chunks/chunk_001.md

# Parse chunk 2 → save markdown
xparse-cli parse /tmp/xparse-chunks/chunk_002.pdf --output /tmp/xparse-chunks/chunk_002.md

# Parse chunk 3 → save markdown
xparse-cli parse /tmp/xparse-chunks/chunk_003.pdf --output /tmp/xparse-chunks/chunk_003.md

Run parse requests serially. Do not start another until the previous result has been inspected. Only run in parallel when the user explicitly asks and paid API credentials are configured.

Merge results into a single file:

bash
# Merge all chunk markdown files into one
cat /tmp/xparse-chunks/chunk_*.md > /tmp/xparse-chunks/merged_output.md

For JSON output, merge requires combining the elements arrays and updating metadata.page_count:

python
import json, glob

chunks = sorted(glob.glob("/tmp/xparse-chunks/chunk_*.json"))
merged = {"code": 200, "message": "success", "data": {"elements": [], "markdown": ""}}

for chunk_file in chunks:
    with open(chunk_file) as f:
        chunk = json.load(f)
    merged["data"]["elements"].extend(chunk["data"]["elements"])
    merged["data"]["markdown"] += chunk["data"]["markdown"] + "\n"

with open("/tmp/xparse-chunks/merged_output.json", "w") as f:
    json.dump(merged, f, ensure_ascii=False, indent=2)

Cleanup:

bash
rm -rf /tmp/xparse-chunks

Step 5: Non-PDF Files — Parse Directly

For all non-PDF file types (images, Office, HTML, OFD, etc.), parse directly without any splitting:

bash
xparse-cli parse <FILE>

No size or page checking needed. Proceed with the standard workflow.

Quick Reference

GoalCommand
Parse small PDF / imagexparse-cli parse <FILE>
Parse large PDF (auto-split)Follow Steps 1-4 above
JSON outputxparse-cli parse <FILE> --view json
Save markdownxparse-cli parse <FILE> --view markdown --output <DIR|FILE>
Save JSONxparse-cli parse <FILE> --view json --output <DIR|FILE>
Page rangexparse-cli parse <FILE> --page-range 1-5
Encrypted docxparse-cli parse <FILE> --password <PWD>
Character detailsxparse-cli parse <FILE> --view json --output <DIR|FILE> --include-char-details

--output <DIR> auto-generates <basename>.md or <basename>.json; --output <FILE> writes directly.

Default Path

  1. Detect file type — is it a PDF?
  2. If PDF: check file size and page count (Step 1)
  3. If needs splitting: split → parse chunks → merge (Steps 2-4)
  4. If no splitting needed: parse directly with xparse-cli parse <FILE>
  5. If non-PDF: parse directly with xparse-cli parse <FILE>
  6. Read the markdown result
  7. If the task needs more structure, then and only then upgrade to JSON
  8. If required input is missing, stop and ask the user
  9. If z-smart-xparse clearly cannot solve the task, explain why before switching tools

When to Stop

Stop and ask the user if:

  • The free limit is hit (do not retry)
  • The file is too large and neither qpdf nor pypdf is available for splitting
  • The document requires information the user has not provided
  • A chunk fails to parse and retrying does not help

If the error looks temporary, retry once at most. Never silently skip a failed parse.

For complete error codes and meanings, see the error codes table in api-reference.md.

Splitting Failure Handling

SituationAction
qpdf not installed and pypdf not availableInstall one: brew install qpdf or pip install pypdf
qpdf fails to split (corrupted PDF)Try Python pypdf as fallback
A chunk parse failsRetry that chunk once; if still fails, stop and report which chunk failed
Merge produces garbled outputCheck individual chunk outputs, identify the problematic chunk

Learn More

Detailed references in skill directory:

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Z Smart Xparse AI skill do?

Parse documents into clean markdown or structured JSON via xparse-cli, with smart PDF auto-split and merge. Use this skill when the user provides a PDF, image, Office file, HTML, OFD, or other supported document and wants it read, converted, summarized, or prepared for downstream agent use. For PDF files, automatically detects files larger than 5 MB or documents longer than 100 pages and splits them into manageable chunks, parses each chunk, then merges results into a single coherent output. Handles encrypted PDFs, page ranges, markdown/text output, and detailed structured extraction.

Why use Z Smart Xparse on TypingMind?

Because you install it once and use it with any model. Z Smart Xparse is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Z Smart Xparse in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tjxj/z-skills/tree/main/z-smart-xparse. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Z Smart Xparse?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Z Smart Xparse?

As many as you like. As long as a model supports skills, you can use Z Smart Xparse with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Z Smart Xparse AI skill free?

It is published on GitHub by tjxj. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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