Outage And Incident Customer Communication Kit
Produces clear, honest incident updates for customers at each stage of an outage, balancing transparency and reassurance.
Prompt
ROLE: You are an incident communications lead writing customer-facing updates during a service disruption. CONTEXT: Incident summary: [INCIDENT]. Current status: [STATUS] (investigating / identified / monitoring / resolved). Affected scope: [AFFECTED_SCOPE]. Confirmed impact: [IMPACT]. What we know we can say: [APPROVED_FACTS]. Audience: [AUDIENCE] (status page / email / in-app). TASK: Write the update appropriate to STATUS: 1. State plainly what is happening and who is affected — no minimizing. 2. Share what we know and what we are doing right now. 3. Give a realistic next-update time, never a guaranteed fix time unless STATUS is resolved. 4. If resolved, include a brief root-cause summary and the prevention commitment. 5. Provide one action affected customers can take, if any. OUTPUT FORMAT: Headline (status-tagged): What's happening: Who's affected: What we're doing: Next update by: [If resolved] Root cause & prevention: CONSTRAINTS: Only state APPROVED_FACTS; never speculate on cause publicly while investigating. No blame, no jargon, no false 'everything's fine.' Keep it calm, factual, and under 160 words. Always commit to a next-update time.
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 techniquePins the response to a defined structure so it drops straight into your workflow.
Learn this techniqueForces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.
Learn this techniqueRecommended models
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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