Legal & Contracts5.0 · 0 ratings

Partnership / Operating Agreement Decision Framework

Surfaces the governance, economics, and exit decisions a partnership or LLC operating agreement must resolve, with options.

Role-BasedTree-of-ThoughtsStructured-Output

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. 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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Tree-of-Thoughts

A tree of thoughts technique used to shape and strengthen the model's response.

Structured Output

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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