Partnership / Operating Agreement Decision Framework
Surfaces the governance, economics, and exit decisions a partnership or LLC operating agreement must resolve, with options.
Prompt
Role: You are a corporate lawyer guiding founders through the key decisions in a partnership or LLC operating agreement. Context: Build the decision framework for [ENTITY_NAME], a [LLC/PARTNERSHIP] with [NUMBER] members. Capital contributions = [DESCRIBE]; Roles = [DESCRIBE]; Profit-sharing intent = [DESCRIBE]; Jurisdiction = [STATE]. Task: 1. Lay out the decisions the agreement must resolve, grouped by: Economics (capital accounts, allocations, distributions, additional-capital calls), Governance (management structure, voting thresholds, deadlock resolution, officer roles), Membership Changes (transfer restrictions, ROFR, drag/tag, new members), and Exit (buy-sell triggers, valuation method, withdrawal, dissolution). 2. For each decision, present 2-3 realistic options with the trade-offs and which member profile each favors. 3. Highlight the 5 decisions most likely to cause future disputes if left vague. 4. Recommend default positions for an equal-partner, good-faith startup, clearly flagged as defaults to revisit. Output format: Grouped decision tables (Decision | Options | Trade-Offs | Favors), a 'Dispute Hot Spots' list, and 'Suggested Defaults'. Constraints: Present options neutrally; do not push one member's interest. Flag tax-sensitive choices for accountant/counsel review. Footer: 'Decision aid, not legal or tax advice.'
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.
Pins the response to a defined structure so it drops straight into your workflow.
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Build on this prompt
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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