contract-review: Skill for Claude Code

clause-segmenter Skill

Segment contract documents into clause-level units and classify each clause.

When to Use

After structural parse (Step 5), at the clause segmentation step (Step 6) of both ingestion and review pipelines.

Segmentation Process

You perform clause segmentation as an LLM judgment task. Follow these rules:

Input

• clean.md — the normalized document text
• structure/outline.json — the structural parse result with section hierarchy
• clause-taxonomy.yaml — the classification taxonomy (from library/policies/)

Segmentation Rules

1. One clause per logical unit: Each substantive section or subsection of the document becomes one clause record. A single numbered section may produce multiple clauses if it contains distinct provisions.

2. Clause type assignment: Assign each clause a clause_type from clause-taxonomy.yaml. Use the taxonomy's category and clause_type IDs exactly. If a clause does not fit any taxonomy entry confidently, assign unmapped. Never guess — unmapped is better than wrong.

3. Preserve original text: The text field must contain the exact source text of the clause. Do not paraphrase, summarize, or modify.

4. Extract cross-references: For each clause, identify references to other sections (e.g., "as defined in Section 5.1", "subject to Clause 3") and record them in cross_refs.

5. Extract defined terms: List any defined terms used within the clause in defined_terms_used.

Output Format

For each clause, produce a JSON file named clause-{NNN}.json:

{
  "clause_id": "clause-001",
  "section_no": "1.1",
  "heading": "Definitions",
  "clause_type": "definitions",
  "text": "...(full clause text)...",
  "defined_terms_used": ["Agreement", "Confidential Information"],
  "cross_refs": ["Section 5.1", "Exhibit A"],
  "paragraph_count": 3
}

Redline Record Enrichment

For documents with doc_class: redline_record, after standard segmentation:

1. Read extraction/changes.json and extraction/comments.json from the document package
2. For each clause, identify changes and comments whose paragraph_index falls within the clause's line range
3. Enrich each clause JSON with a redline_data field: