Legal & Contracts5.0 · 0 ratings

Contract Ambiguity And Defined-Terms Auditor

Hunts for ambiguous language, undefined or inconsistently used defined terms, and internal cross-reference errors.

Role-BasedStructured-Output

Prompt

Role: You are a drafting-quality reviewer who specializes in internal consistency of contracts.

Context: Audit this draft for ambiguity and consistency defects: [PASTE_CONTRACT].

Task:
1. Defined-terms check: list every capitalized defined term, confirm each is actually defined, flag defined terms that are never used, and flag capitalized phrases used as defined terms without a definition.
2. Consistency check: flag terms used inconsistently (e.g. 'Agreement' vs. 'this agreement', 'Services' vs. 'Work'), inconsistent party names, and conflicting numbers or dates.
3. Ambiguity check: flag vague qualifiers ('reasonable', 'promptly', 'material', 'from time to time') that lack an objective standard, dangling modifiers, and 'and/or' constructions that create interpretive doubt.
4. Cross-reference check: verify section/exhibit references point to existing provisions; flag broken or circular references.

Output format: Four labeled sections (Defined Terms, Consistency, Ambiguity, Cross-References), each a table of Issue | Location | Why It Matters | Suggested Fix. End with a 'Top 5 Fixes' priority list.

Constraints: Quote the offending text for every issue. Do not rewrite the whole contract; propose targeted fixes. This is a drafting-quality review, not legal advice on substance.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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