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Draft an uptime SLA with service credits for my SaaS product

A customer-facing service level agreement with a measurable uptime target, exclusions, credit table, and claim process.

Legal & ComplianceFew-ShotStandardLegalWritePlanFill-in Template

The prompt

Draft a service level agreement (SLA) for my SaaS product. Product and plans covered: [e.g. "Enterprise plan only"] Uptime target we can actually meet: [e.g. 99.9% monthly] and our last 12 months of actual uptime: [DATA or "unknown"] How we measure availability: [status page, synthetic checks, error rates - what we have today] Planned maintenance practice: [windows, notice period] Support response targets, if included: [by severity] Credit appetite: [e.g. "credits capped at 25% of monthly fees"] Include: 1. Definitions: availability, downtime, monthly uptime percentage (show the formula), scheduled maintenance, severity levels. 2. Exclusions: customer-caused issues, third-party services, force majeure, beta features, scheduled maintenance with notice. 3. A service credit table tied to uptime bands, with a cap. 4. Claim process: how and within how many days to request credits, what evidence is needed. 5. Credits as the sole remedy, plus an optional termination right for repeated failures (flag it as a negotiation lever). 6. Support response and resolution targets by severity, if I gave them. Also give me: - The allowed downtime per month and per year for my target (e.g. 99.9% is about 43 minutes a month). - A warning if my target is higher than my history supports. - Monitoring and reporting I need in place before publishing this. Use plain language. Mark anything I have not confirmed as [CONFIRM]. This is general information - have a lawyer review it against my master agreement before use.

Highlighted [brackets] are blanks to replace with your own details.

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What to fill in

  • e.g. "Enterprise plan only"
  • e.g. 99.9% monthly
  • DATA or "unknown"
  • windows, notice period
  • by severity
  • e.g. "credits capped at 25% of monthly fees"
  • CONFIRM

How this prompt is built

This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.

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