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marker

marker

Use Marker to convert documents, configure pipelines, run LLM extraction, and operate app/server deployment surfaces.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentación de la Skill

GitHub

name: marker description: "Use Marker to convert documents, configure pipelines, run LLM extraction, and operate app/server deployment surfaces." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Marker Repo Skill

Use this repo skill when a user asks about Marker, marker-pdf, marker_single, marker, document-to-markdown/JSON/HTML/chunks conversion, OCR/table conversion, structured extraction, Marker LLM services, custom Marker processors/renderers/providers, or Marker app/server deployment.

Start Here

  1. Confirm the user wants the open-source Marker package, distributed as marker-pdf and imported as marker.

  2. For a fresh environment, install the base package first:

    pip install marker-pdf
    
  3. Install marker-pdf[full] only when converting non-PDF document families such as DOCX, PPTX, XLSX, HTML, or EPUB.

  4. Run a safe environment probe before heavy conversion, model downloads, or service launch:

    python scripts/marker_environment_check.py --check-cli
    
  5. Route to the focused sub-skill below, then use its nearest references/scripts for commands, API examples, validation, and troubleshooting.

Route By Task

User taskRead
Convert one PDF/image or a folder, choose output format, use Python API, run table-only/OCR-only conversion, parse outputs, tune workers/devicesub-skills/conversion-cli-api/SKILL.md
Explain or change config_json, ConfigParser, --processors, --converter_cls, providers, builders, processors, renderers, schema/debug outputsub-skills/configuration-extension/SKILL.md
Enable --use_llm, select Gemini/Vertex/Ollama/Claude/OpenAI/Azure services, build structured extraction schemas, troubleshoot LLM JSON/retry/key failuressub-skills/llm-extraction-services/SKILL.md
Run marker_server, call FastAPI endpoints, use marker_gui/marker_extract, adapt Modal deployment, build client templatessub-skills/server-deployment/SKILL.md

Shared References

  • references/install-and-environment.md: install variants, optional dependencies, backend/device checks, model/download cautions, and package identity.
  • references/troubleshooting.md: cross-cutting install/import, optional dependency, device, model/cache, credential, and workflow routing failures.
  • references/benchmark-notes.md: performance and benchmark context without making benchmark scripts a runtime dependency.
  • references/repo-provenance.md: source snapshot and evidence paths used to generate this skill.
  • references/repo-routing-metadata.json: structured routing metadata for DisCo import.

Safety Defaults

  • Do not run document conversion, model downloads, server processes, Streamlit apps, Modal deploys, or external LLM calls unless the user explicitly asks.
  • Prefer --help, dry-run config probes, schema validation, and small fixture checks before heavy conversion.
  • Treat original repo examples/tests as evidence only; this skill bundles its own references and scripts for future use.
  • Keep API keys and local environment paths out of generated code, prompts, logs, and shared examples.
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