Commercial Clause Extraction

Commercial Clause Extraction

Overview

Perform NLP-based clause extraction from commercial contracts, identifying, classifying, and tagging all contractual clauses with source references for downstream commercial operations.

Announce at start: "I'm using the commercial-clause-extraction skill to extract clauses from the contract document."

When to Use This Skill

Trigger Conditions:

• New contract received requiring clause analysis
• Contract amendment requires clause re-evaluation
• Obligation tracking needs clause source identification
• Compliance monitoring requires clause reference verification

Prerequisites:

• Contract document available in text or searchable PDF format
• Contract metadata available (contract number, parties, effective date)
• Clause index or clause dictionary available for reference

Step-by-Step Procedure

Step 1: Document Preparation

1. Verify contract document is complete (all pages, annexures, schedules)
2. Convert to text format if necessary (OCR for scanned documents)
3. Identify document sections and structure
4. Verify contract metadata (contract number, parties, dates)

Step 2: Clause Boundary Detection

Apply clause boundary detection:

1. Identify section headers and numbering
2. Detect paragraph-level clause boundaries
3. Identify sub-clause hierarchy (numbering patterns: 1, 1.1, 1.1.1)
4. Flag ambiguous boundaries for manual review

Step 3: Clause Classification

Classify each identified clause into commercial clause categories:

Step 4: Clause Extraction

For each classified clause:

1. Extract clause text verbatim
2. Record source location (section number, page number, paragraph)
3. Identify key data elements within clause:
   • Monetary values (amounts, rates, caps)
   • Time periods (notice periods, durations, deadlines)
   • Conditions (triggers, requirements, exceptions)
   • References (to other clauses, documents, standards)
4. Tag with clause category and classification confidence

Step 5: Reference and Cross-Reference Tagging

1. Identify intra-contract references (clause-to-clause references)
2. Identify external references (standards, regulations, other documents)
3. Create cross-reference map for all identified references
4. Flag broken or missing references for manual review

Step 6: Obligation Identification

1. From payment terms: Extract payment obligations, amounts, schedules
2. From performance clauses: Extract deliverable obligations, standards
3. From compliance clauses: Extract regulatory obligations
4. From termination clauses: Extract notice obligations, handover obligations
5. Tag each obligation with source clause reference

Step 7: Structured Output

Generate structured JSON output:

{
  "contract_id": "CON-2026-XXXX",
  "extraction_date": "2026-04-01T20:00:00Z",
  "total_clauses_extracted": 0,
  "clauses": [
    {
      "clause_id": "CL-001",
      "section_number": "12.3",
      "clause_category": "Payment Terms",
      "clause_text": "...",
      "page_number": 0,
      "key_elements": {
        "monetary_values": [],
        "time_periods": [],
        "conditions": [],
        "references": []
      },
      "obligations_identified": ["OBL-001", "OBL-002"],
      "confidence": 0.95
    }
  ],
  "cross_references": [],
  "summary": {
    "by_category": {},
    "obligations_count": 0,
    "critical_clauses_count": 0
  }
}

Step 8: Validation and Quality Check

1. Verify all clause categories are represented
2. Check that critical clauses (payment, LD, termination) are extracted
3. Validate that cross-references resolve within the document
4. Confirm obligation extraction completeness
5. Flag low-confidence extractions (<80%) for human review

Success Criteria

• All contract sections processed
• Critical clause categories identified (payment, LD, termination, variation, dispute)
• Each clause tagged with source location (section, page)
• Key elements extracted (monetary values, time periods, conditions, references)
• Cross-reference map generated
• Obligations identified and linked to source clauses
• Low-confidence extractions flagged for human review
• Structured output generated and validated

Common Pitfalls

1. Scan Quality Issues — Poor OCR quality leads to misidentified clause boundaries. Always verify OCR accuracy before extraction.
2. Annexure/Schedule Separation — Clauses in annexures and schedules are often missed. Ensure all document components are processed.
3. Cross-Reference Resolution — Many contracts reference clauses that don't exist or use informal references. Flag all unresolved references.
4. Hidden Obligations — Some obligations are embedded within non-obligation clauses (e.g., notice requirements in dispute clauses). Review thoroughly.
5. Version Mismatch — Ensure the document being processed matches the executed version. Check dates, signatures, and amendment references.

Cross-References

Related Skills

• commercial-contract-interpretation — Clause interpretation and meaning analysis
• commercial-obligation-tracking — Obligation lifecycle management
• commercial-compliance-monitoring — Compliance against extracted clauses

Related Agents

• COM-007 Commercial Clause Extraction Agent — Primary agent
• COM-002 Commercial Contract Administrator Agent — Supporting agent