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Docling skill

Skill realraelrr/docling-skill

Agent-first document ingestion layer on Docling with Markdown, image sidecars, manifests, OCR, and quality gating.

Install
npx -y skills add realraelrr/docling-skill

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 2 stars2 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Use when an agent needs to convert local PDF, Office, spreadsheet, HTML, text, Markdown, or image files into docling-skill source.* sidecars before downstream reasoning, retrieval, wiki ingestion, or handoff.

SKILL.md

4.2 KB, as published. Nobody here has run it

docling-skill

Use docling-skill as the local ingestion gate for document files. It produces an agent-only v2 source.* sidecar set and a compact manifest that must be checked before any agent consumes the content.

Use When

  • Input is a local file: pdf, docx, pptx, xls, xlsx, csv, html, txt, md, png, jpg, jpeg, tif, tiff, bmp, or webp.
  • Downstream work needs Markdown plus on-demand quality evidence, structured Docling output, or image sidecars.
  • The agent needs to decide whether conversion output is safe enough to use.

Do Not Use When

  • The source is a remote URL; fetch or browser capture belongs upstream.
  • The task is chunking, summarization, tagging, embedding, or knowledge modeling.
  • The file is .doc, .ppt, .xlsm, password-protected, corrupt, or a workbook that needs manual semantic preprocessing; ask for a clean .docx, .pptx, .xlsx, .csv, or PDF.

Run

Always provide an explicit output directory.

conda run -n docling python -m docling_skill.cli "<input_path>" "<output_dir>"

If the CLI is installed directly:

docling-skill "<input_path>" "<output_dir>"

PDF OCR flags, only when needed:

--ocr-engine auto|tesseract|ocrmac|rapidocr
--ocr-lang <lang>  # repeatable or comma-separated
--force-full-page-ocr
--no-ocr-remediation
--pdf-audit  # optional evidence flag for eligible native formats; renderer support is soft/unavailable by default

Outputs

Expected files:

  • source.manifest.json
  • source.md
  • source.evidence.json

Read source.manifest.json first, then follow decision.read_order.

  • Low-risk good output normally has read_order: ["source.md"].
  • Warning, salvaged, and failed_for_agent output points to source.evidence.json.
  • Use source.evidence.json for structure recovery, quality signals, attempts, page/slide/sheet coverage, spreadsheet metadata, and image placeholders such as [[image:picture-p2-1]].

Do not add downstream fields such as tags, keywords, categories, summaries, embeddings, or chunk IDs to source.manifest.json or source.evidence.json.

Manifest Decision

Inspect these groups:

  • Contract: contract_version, producer
  • Decision: decision.status, decision.risk_level, decision.agent_ready, decision.read_order
  • Source: source.input_type, source.pipeline_family, source.title
  • Evidence pointer: artifacts.evidence, warnings, reasons, counts

Decision matrix:

Manifest decisionAgent action
good + lowUse source.md as primary input.
good + mediumUse source.md, but inspect source.evidence.json before relying on details.
salvagedUse only as OCR-remediated medium-risk output; inspect evidence.
failed_for_agentDo not present as clean ingestion; report failure evidence from source.evidence.json.

agent_ready: true means default-usable, not semantically proven.

Format Checks

  • PDF: inspect evidence quality.signals.page_coverage when page warnings exist, especially failed_pages and first_page_failed.
  • Chinese-heavy output: inspect evidence quality.signals.text_normalization and quality.signals.text_integrity.
  • Spreadsheets: use evidence structured_document and spreadsheet when merged cells, multi-sheet layout, spans, or offsets matter; Markdown is only a preview.
  • Images: image-only output with no usable OCR text should be treated as high risk when the manifest says failed_for_agent.
  • Figures/charts: resolve placeholders through evidence images; image extraction is not universal across formats.

Success Signal

  • Command exits 0.
  • All three v2 source.* files exist in the output directory.
  • Manifest has been checked before using source.md.

Failure Report

When ingestion is not clean, report:

  • input path and input type
  • command exit code or exception
  • manifest decision.status, decision.risk_level, reasons, warnings
  • relevant evidence quality.signals
  • evidence selected_attempt and whether OCR remediation was applied

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.