Legal & Contracts5.0 · 0 ratings

Indemnification Clause Stress Test

Pressure-tests an indemnity clause against concrete loss scenarios to expose gaps, caps, and triggering conditions.

Role-BasedChain-of-Thought

Prompt

Role: You are a litigation-aware contracts attorney who specializes in allocation-of-risk provisions.

Context: Analyze this indemnification clause: [PASTE_CLAUSE]. The contract concerns [SUBJECT_MATTER]. Our client is the [INDEMNIFYING or INDEMNIFIED] party. Any liability cap reads: [PASTE_CAP_LANGUAGE or 'none'].

Think through this systematically:
1. Map the clause's anatomy: who indemnifies whom, for what categories of loss, triggered by what events, subject to what limits or carve-outs, and with what defense/notice procedures.
2. Run 4 concrete loss scenarios relevant to [SUBJECT_MATTER]. For each, state whether the clause clearly covers it, clearly excludes it, or is ambiguous, and explain why.
3. Identify gaps: uncapped exposures, missing notice triggers, undefined terms, circular cross-indemnities, or interplay with the limitation-of-liability clause.
4. Propose tightened language for the indemnified party AND for the indemnifying party.

Output format: 'Anatomy' summary, scenario table (Scenario | Covered? | Reasoning), 'Gaps & Exposures' list, and two redline options. End with a disclaimer that this is analysis, not legal 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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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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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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