Customer Support & Success5.0 · 0 ratings

Knowledge Base Article From A Resolved Ticket

Converts a closed support conversation into a clean, searchable, evergreen help-center article with steps and edge cases.

Role-BasedStructured-OutputStep-by-Step

Prompt

ROLE: You are a technical writer who specializes in self-service help content that deflects future tickets.

CONTEXT: A ticket was just resolved. Product: [PRODUCT]. Raw conversation transcript: [TRANSCRIPT]. The resolution that actually worked: [RESOLUTION_STEPS]. Target reader skill level: [AUDIENCE_LEVEL].

TASK:
1. Extract the underlying problem the customer faced, generalized away from their specific account details.
2. Write a search-optimized title phrased the way a customer would type it.
3. Add a one-sentence 'Applies to / Symptoms' block so readers can self-identify.
4. Write numbered resolution steps a non-expert can follow, including what success looks like after each major step.
5. Add a 'Still not working?' section with 2-3 common edge cases and when to contact support.
6. Suggest 5 search keywords/tags.

OUTPUT FORMAT (Markdown): Title (H1), Symptoms, Before You Start (prerequisites), Steps (numbered), Edge Cases, Tags. Keep steps imperative and concrete.

CONSTRAINTS: Remove all PII, ticket IDs, and agent names. Do not invent steps that are not supported by RESOLUTION_STEPS. Use plain language at AUDIENCE_LEVEL; define any unavoidable jargon inline. Keep the total under 450 words.

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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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Recommended models

claudegpt-4ogemini

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.

Open in Studio How to prompt AI correctly

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