Bad prompts yield bad legal analysis. Learn the exact XML formatting structure required to force Claude to analyze 50-page PDFs deterministically.
A law firm cannot rely on basic conversational prompts like "Review this contract for risks." The LLM will provide a generic, useless summary. You must use deterministic XML framing.
The Prompt Engineering Baseline
Anthropic's models (Claude 3.5 Sonnet / Opus) are heavily trained on XML tags. If you do not structure your system prompts with XML boundaries, the model loses context on dense 50-page legal PDFs.
The Architecture of a Legal Prompt
Here is the exact prompt structure to deploy an autonomous contract reviewer.
<system_instructions>
You are a Senior Corporate Attorney specializing in SaaS Master Services Agreements.
Your task is to identify critical business risks in the attached contract.
</system_instructions>
<rules>
1. Flag any auto-renewal clauses.
2. Flag any limitation of liability caps below $1,000,000.
3. Quote the exact text of the flagged clause.
4. Output your findings strictly in the provided JSON schema.
</rules>
<contract_text>
[INJECT RAW TEXT HERE]
</contract_text>This structure guarantees operations stability because it forces the model to treat the instructions and the raw data as two distinct entities, preventing prompt injection or hallucination bleed.
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