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Oma Pdf

OrganizationPopular
first-fluke
oma-pdf

Extract PDF text, headings, tables, and images into Markdown using opendataloader-pdf. Use for PDF parsing, not PDF layout creation.

Overview

Publisherfirst-fluke
Repositoryoh-my-agent
Skill nameoma-pdf
Stars
1.3K
Forks
149
Bundled files
2
LicenseMIT
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.

  • 2 bundled files

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

  • Open source

    Published by first-fluke on GitHub. Read the source before you install it.

Installation

Install the Oma Pdf 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.
  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/first-fluke/oh-my-agent.git /tmp/oh-my-agent
mkdir -p .claude/skills
cp -r /tmp/oh-my-agent/skills/oma-pdf .claude/skills/oma-pdf
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Oma Pdf 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 Oma Pdf 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 Oma Pdf 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.

PDF Skill - PDF to Markdown Conversion

Scheduling

Goal

Convert PDF files into structured Markdown or another requested extraction format while preserving readable document structure for LLM context, RAG, or downstream review.

Intent signature

  • User asks to convert, parse, read, extract, or transform a PDF.
  • User needs PDF text, headings, lists, tables, or images prepared for AI consumption.
  • User mentions "PDF to markdown", "parse PDF", "read this PDF", or equivalent wording.

When to use

  • Converting PDF documents to Markdown for LLM context or RAG
  • Extracting structured content such as tables, headings, lists, images, footnotes, or hyperlinks
  • Preparing PDF data for AI consumption
  • Checking whether a PDF has a text layer before choosing OCR

When NOT to use

  • Generating or creating PDFs -> use document-generation tools
  • Editing existing PDFs -> out of scope
  • Reading an already-text file -> use direct file reading
  • Processing HWP, HWPX, DOCX, XLSX, or slide decks -> use the matching document skill

Expected inputs

  • input_path: PDF file or folder path
  • output_dir: optional target directory
  • format: optional output format, default markdown
  • ocr_languages: optional OCR language list for scanned or image-based PDFs
  • extraction_options: optional flags for tagged structure, image extraction, or hybrid conversion

Expected outputs

  • Markdown, text, JSON, HTML, or combined extraction output
  • Normalized Markdown when Markdown is produced
  • A short report with output path, page count, and conversion issues

Dependencies

  • uvx opendataloader-pdf for standard conversion
  • uvx --from "opendataloader-pdf[hybrid]" opendataloader-pdf-hybrid for OCR or hybrid conversion (the hybrid server is a console script of the [hybrid] extra, not a standalone package)
  • uvx mdformat for Markdown normalization
  • Local filesystem access to input and output paths
  • Optional OCR runtime via the hybrid server

Control-flow features

  • Branches on text-layer quality, tagged PDF availability, scan/OCR needs, and user-requested output format
  • Calls external CLI tools through uvx
  • Reads local files and writes local extraction outputs
  • Uses a hybrid server only when OCR or complex extraction needs justify it

Structural Flow

Entry

  1. Confirm that the input path exists and is a PDF file, PDF folder, or supported batch input.
  2. Check file size and warn when the input is large enough to risk slow conversion or memory pressure.
  3. Resolve output_dir and the expected output filename.

Scenes

  1. PREPARE: Validate the input path, output target, and requested extraction options.
  2. ACQUIRE: Assess whether the PDF has a readable text layer by extracting a text preview.
  3. ACT: Convert using standard mode, tagged-structure mode, or hybrid OCR mode.
  4. VERIFY: Run mdformat for Markdown output and inspect the result for readable structure.
  5. FINALIZE: Report output path, page count, format, and any extraction quality issues.

Transitions

  • If the preview text is readable, use standard conversion.
  • If the PDF is tagged and standard output is garbled, retry with --use-struct-tree.
  • If tables are missing or broken, retry with --table-method cluster or --markdown-with-html before escalating to hybrid mode.
  • If the PDF is scanned or image-based, start or reuse the hybrid OCR server and convert with hybrid mode.
  • If conversion fails because the PDF is encrypted, stop and ask for the password or an unlocked copy.
  • If conversion hits memory or size limits, process smaller page ranges into distinct output directories (or append --to-stdout) so repeated runs do not overwrite the same basename.

Failure and recovery

FailureRecovery
uvx unavailableAsk user to install uv before conversion
opendataloader-pdf-hybrid not foundInvoke via uvx --from "opendataloader-pdf[hybrid]" opendataloader-pdf-hybrid; the bare package name does not exist on PyPI
Password-protected PDFAsk for password or unlocked PDF
Garbled outputRetry with tagged structure or hybrid mode
Missing tablesRetry with --table-method cluster or --markdown-with-html first; hybrid mode for scanned tables
OCR language mismatchRetry with explicit OCR languages, for example ko,en
Large file or memory pressureSplit into page ranges using distinct output directories or --to-stdout; never reuse one output directory for the same basename

Exit

  • Success: output file exists, Markdown is formatted when applicable, and extracted structure is readable.
  • Partial success: output exists but quality issues are reported explicitly.
  • Failure: no reliable output is produced and the blocking cause is reported.

Logical Operations

Actions

ActionSSL primitiveEvidence
Validate path and optionsVALIDATEInput preflight in execution protocol
Probe text layerREADText preview extraction
Choose conversion strategySELECTStandard, tagged, or hybrid mode decision
Run converterCALL_TOOLuvx opendataloader-pdf
Start OCR serverCALL_TOOLuvx --from "opendataloader-pdf[hybrid]" opendataloader-pdf-hybrid
Write output artifactWRITEMarkdown, text, JSON, or HTML output
Normalize MarkdownCALL_TOOLuvx mdformat
Inspect extraction qualityVALIDATEStructure/readability verification
Report resultNOTIFYFinal user-facing summary

Tools and instruments

  • opendataloader-pdf: primary PDF extraction CLI
  • opendataloader-pdf-hybrid: hybrid OCR and complex extraction path
  • mdformat: Markdown normalization
  • Filesystem commands such as file, wc, or pdfinfo may be used for preflight when available

Canonical command path

bash
uvx opendataloader-pdf "{input_path}" -f text --pages 1-3 --to-stdout -q   # text-layer probe (no temp files)
uvx opendataloader-pdf "{input_path}" --format markdown --output-dir "{output_dir}"
uvx mdformat "{output_path}"

For scanned/image-based PDFs, start OCR first and then convert through hybrid mode:

bash
uvx --from "opendataloader-pdf[hybrid]" opendataloader-pdf-hybrid --port 5002 --force-ocr --ocr-lang "{languages}"
uvx opendataloader-pdf --hybrid docling-fast --hybrid-mode full "{input_path}" --format markdown --output-dir "{output_dir}"

On-request flags — --sanitize (PII masking), --pages (range extraction), --threads (parallel pages), --detect-strikethrough, hybrid --enrich-formula / --enrich-picture-description — are detailed in resources/execution-protocol.md. The two enrichment flags require client-side --hybrid-mode full.

Resource scope

ScopeResource target
LOCAL_FSInput PDFs and generated output files
PROCESSuvx subprocesses and optional hybrid server
MEMORYExtracted previews and validation notes
OTHEROCR model/runtime behavior inside hybrid mode

Preconditions

  • The input PDF path exists and is readable.
  • The output location is writable or can be created.
  • Required CLIs are available through uvx.
  • OCR is only attempted when hybrid mode is available or can be started.
  • Defaults come from the pdf: section of .agents/oma-config.yaml, falling back to config/pdf-config.yaml for unset keys; explicit user options override both, and output.overwrite: false requires confirmation before replacing an existing output file.

Effects and side effects

  • Creates or overwrites extraction output depending on configuration and user intent.
  • May start a local hybrid OCR server on the configured port.
  • May consume significant CPU, memory, or time for large or scanned PDFs.
  • Does not intentionally modify the source PDF.

Guardrails

  1. Do not invent missing content when extraction is incomplete.
  2. Always report garbled text, missing tables, OCR uncertainty, or partial extraction.
  3. Prefer standard conversion first when the text layer is readable.
  4. Use OCR only when the PDF is scanned, image-based, or standard extraction quality is insufficient.
  5. Keep detailed command sequences in resources/execution-protocol.md rather than duplicating every variant here.

References

  • Execution protocol: resources/execution-protocol.md
  • Configuration: read the pdf: section of .agents/oma-config.yaml first, then fall back to config/pdf-config.yaml for any key it does not set. User overrides belong in .agents/oma-config.yaml, since oma update overwrites the skill config.
  • Context loading: ../_shared/core/context-loading.md
  • Quality principles: ../_shared/core/quality-principles.md

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 Oma Pdf AI skill do?

Extract PDF text, headings, tables, and images into Markdown using opendataloader-pdf. Use for PDF parsing, not PDF layout creation.

Why use Oma Pdf on TypingMind?

Because you install it once and use it with any model. Oma Pdf 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 Oma Pdf in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/first-fluke/oh-my-agent/tree/main/skills/oma-pdf. 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 Oma Pdf?

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 Oma Pdf?

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

Is the Oma Pdf AI skill free?

Yes. It is published on GitHub by first-fluke under the MIT license. 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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