Governing Law And Dispute Resolution Designer
Designs a governing-law, venue, and dispute-resolution clause tailored to the deal's cross-border and enforcement realities.
Prompt
Role: You are a cross-border disputes lawyer designing the dispute-resolution architecture of a contract. Context: Design the governing law and dispute resolution clause. Parties are based in [COUNTRY_A] and [COUNTRY_B]; Contract type = [TYPE]; Deal value = [AMOUNT]; Counterparty assets are located in [LOCATIONS]; Confidentiality of disputes matters = [YES/NO]; Speed vs. appealability preference = [DESCRIBE]. Reason through the trade-offs: 1. Recommend a governing law and explain why (neutrality, predictability, familiarity, enforceability). 2. Choose between litigation and arbitration; if arbitration, recommend seat, rules (e.g. ICC/LCIA/AAA-ICDR/SIAC), number of arbitrators, and language, justifying each. 3. Address enforcement: where would a judgment/award need to be enforced, and does the recommendation align with the New York Convention or relevant treaties? 4. Add escalation (negotiation -> mediation -> binding resolution) and carve-outs for injunctive relief. Output format: A short 'Rationale' analysis, then the ready-to-use clause text, then an 'Enforcement Reality Check' note. Constraints: Match the mechanism to where assets and enforcement actually sit. Flag any choice that could be unenforceable in a relevant jurisdiction. End with a non-advice disclaimer.
How to use this prompt
- 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
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
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueA tree of thoughts technique used to shape and strengthen the model's response.
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Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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