---

name: import-pdf-processing-anthropic
description: Use when migrating a PDF document-processing skill originally built for the Anthropic Claude API into the mini-claude-for-legal format. The adapter maps legacy PDF extraction configuration — text layer parsing, OCR fallback, table extraction, form field reading, and annotation handling — into the standard skill model. Critical for legal workflows involving court filings, regulatory submissions, notarised documents, and scanned contracts.
license: MIT
metadata:
id: import.pdf-processing-anthropic
category: import
jurisdictions: [multi]
priority: P3
intent: [import, pdf, document-processing, migration, anthropic]
related: [import-docx-processing-anthropic, import-pptx-processing-anthropic, import-contract-review-anthropic, multimodal-document-ingestion]
source: Louis — HAQQ Legal AI (github.com/sboghossian/mini-claude-for-legal)
version: "1.0"

Import: PDF Processing (Anthropic)

What it does

This import adapter migrates a PDF document-processing skill originally built for Anthropic's Claude API into the mini-claude-for-legal standard format. PDF is the dominant format for legal documents globally: court filings, notarised instruments, regulatory submissions, signed contracts, government-issued licences, and certified translations all arrive as PDFs.

Unlike DOCX, PDFs may or may not have a selectable text layer. Scanned documents require OCR; encrypted PDFs require a password; form PDFs have interactive fields; certified documents may have a digital signature that must be preserved. The Anthropic-native skill may have used Claude's native PDF vision capability, a dedicated extraction library, or both.

Import config

Field	Source mapping	Default if absent
extraction_mode	Legacy mode	text_first_ocr_fallback
ocr_engine	Legacy ocr	auto (system default)
tables	Legacy extract_tables boolean	true
form_fields	Legacy extract_forms boolean	true
annotations	Legacy extract_annotations boolean	true
digital_signature_check	Legacy check_signature boolean	true
language	Legacy lang	auto-detect
rtl_support	Legacy rtl boolean	true (for MENA)
chunk_size	Legacy chunk_tokens	2000
overlap	Legacy overlap_tokens	200
output_format	Legacy format	markdown

Dry-run preview

IMPORT PREVIEW — pdf-processing-anthropic
Source shape     : Anthropic PDF extraction config
Mode             : text_first_ocr_fallback
OCR              : auto
Tables           : extracted
Form fields      : extracted
Annotations      : extracted
Digital signature: checked (not verified cryptographically — visual only)
RTL              : enabled (Arabic/Hebrew support)
Chunk            : 2000 tokens / 200 overlap
Output           : markdown

Extraction pipeline (post-import)

1. Detect PDF type:

   • Native (selectable text) → direct text extraction
   • Scanned image → OCR pipeline
   • Mixed (some pages scanned, some native) → page-by-page detection
   • Encrypted → request password; log attempt; never store password

2. Page-by-page extraction: maintain page-number metadata for every extracted element; legal documents frequently reference "page X, clause Y".

3. Table extraction: detect table boundaries; serialize to markdown pipe tables; flag tables with merged cells as [COMPLEX TABLE — manual verification recommended].

4. Form field extraction: identify interactive PDF form fields; extract field names and values; flag unsigned or blank required fields.

5. Annotation extraction: extract highlighted text, comments, and sticky notes; attribute to author if metadata available; append as footnote block.

6. Digital signature check: detect presence of digital signature (visual check only — not cryptographic validation); flag signed documents separately.

7. RTL handling: detect right-to-left text (Arabic, Hebrew); preserve paragraph ordering; ensure column order in tables reflects RTL layout.

8. Chunking: split by token count with overlap; preserve clause boundaries where possible.

Legal document types and special handling

Document type	Special requirement
Court filing (Lebanon / UAE)	Page/paragraph numbering must be preserved; filing stamps and seals should be flagged
Notarised document	Notary signature block and certification text must be extracted intact
Certified translation	Translator certification page must be preserved as a separate block
Government licence / certificate	Issue date, expiry date, and licence number should be extracted as structured metadata
Board resolution / POA	Signatory block and witness/notary endorsement are legally significant
Regulatory submission	Submission reference number and date should be extracted as metadata

Arabic / bilingual PDF considerations

PDFs from MENA jurisdictions frequently mix Arabic (RTL) and English (LTR) text:

• Set rtl_support: true to handle RTL paragraphs
• In bilingual contracts, Arabic is often the prevailing language (UAE and KSA government contracts); flag and note the prevailing language
• OCR quality for Arabic varies by font and scan quality; flag low-confidence passages

Failure modes

Error	Likely cause	Resolution
no_text_layer	Scanned PDF without OCR	Switch to OCR mode; warn user of quality risk
password_protected	Encrypted PDF	Prompt for password; never log
rtl_reversal	RTL paragraphs extracted as LTR	Ensure rtl_support: true
table_parse_fail	Complex merged-cell tables	Flag for manual review
signature_not_found	Digital signature present but not detected	Flag as [SIGNATURE STATUS UNKNOWN]
arabic_ocr_low_quality	Poor scan of Arabic text	Warn user; recommend re-scan at 300 DPI minimum

Related skills

• [[import-docx-processing-anthropic]]
• [[import-pptx-processing-anthropic]]
• [[import-contract-review-anthropic]]
• [[multimodal-document-ingestion]]
• [[review-contract-generic]]