Prompt

LegalPromptFree

NDA Red-line — Vendor-Sent

Flag the clauses that matter: mutuality, term, IP carveouts, governing law.

  • Role-Based
  • Chain-of-Thought
  • Output-Format
Download .mdOpen in Studio~204 words
**Role:** In-house counsel at a 200-person SaaS. You've reviewed 500+ vendor NDAs and you know which clauses vendors slip in hoping you won't notice.

**Context:** Vendor: [name]. Relationship: [we'll receive their data | they'll receive our data | mutual exchange]. Term needed: [length]. Their proposed NDA: [paste]. Our standard mutual NDA template: [reference].

**Task:** Walk the NDA section by section.

1. For each potentially problematic clause: quote the offending language verbatim, explain the risk in one sentence, propose specific replacement language.
2. Flag asymmetry explicitly — unilateral when it should be mutual, narrow definition of confidential info, expansive carveouts.
3. Check: term length, definition of Confidential Information, exclusions (especially residual knowledge clauses), governing law / jurisdiction, return-of-materials, injunctive relief.
4. Distinguish "must fix" from "nice to fix" — be explicit. Some asymmetry is acceptable for the size of the deal.
5. End with a top-3 "must fix before signing" list.

**Constraints:**
- Cite the section number for each issue
- Quote the offending language exactly
- Propose specific replacement text, not "make this mutual"
- Distinguish must-fix from nice-to-fix
- Never give generic legal advice

**Output format:** Per-section table — 3 columns: Original / Risk / Proposed Redline · plus top-3 "must fix" summary.

How to use it

  1. Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer. The Studio lists the blanks for you and can add your project's background.
  2. Copy it (or download the .md) and paste it into the AI you already use — it knows your work, so that is where the prompt does the most.
  3. Not sure what it produces? Give it a test run in the Studio first, then refine 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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Chain-of-Thought

Asks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.

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Output-Format

Specifies the exact shape of the result — sections, a table, JSON, a word count — so the output is predictable and ready to use.

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Works with

Any chat AI — ChatGPT, Claude, Gemini, Copilot, Grok, Mistral or a local model. The structure does the work, so you are not tied to one vendor or one model version.

New to structured prompts? Start with how to prompt AI, the RCTCO prompt framework this prompt is built on, and role prompting examples.

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