Decide SaaS Service Credits Fairly

    by Mariusz Wrzeszczynski

    1

    Review SaaS service-credit claims after outages or SLA failures without guessing or damaging trust.

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    Works with the AI tools you already use

    CClaude CodeCCursorCCodex CLIGGitHub CopilotGGemini CLIVVS CodeWWindsurfMManus+14 more

    See it in action

    You say

    Review a claim from Acme Corp for a 4-hour outage on Oct 12. Their SLA says 99.9% uptime. Monthly fee is $5k. Our logs show 120 mins downtime, but 60 mins was scheduled maintenance.

    Your agent does

    Service Credit Decision: No Contractual Credit.

    The 99.9% threshold allows for 43 mins of downtime/month. With 60 mins of excluded maintenance, only 60 mins of downtime count. Since this exceeds the 43-min limit, a credit of $250 (5%) is recommended. Goodwill review suggested for the extra impact.

    What you get

    Reconcile vendor logs with customer evidence to verify downtime.Apply complex credit formulas and caps across different service tiers.Identify valid exclusions like scheduled maintenance or third-party failures.Generate ready-to-send customer responses for approved or denied claims.Create internal audit trails for financial approval and corrective actions.

    About this skill

    The problem

    Manually reviewing SaaS service credit claims is slow, error-prone, and often leads to inconsistent financial concessions. Teams struggle to reconcile conflicting uptime data with complex, negotiated SLA terms while under pressure from customers.

    What it does

    • Analyzes customer claims against specific contract terms, order forms, and SLA policies.
    • Reconciles vendor monitoring data with customer-provided evidence to verify performance breaches.
    • Calculates precise credit amounts based on contract formulas, tiers, and maximum caps.
    • Separates contractual entitlements from discretionary goodwill gestures to protect margins.
    • Generates structured internal decision records and professional, ready-to-send customer responses.

    Why this beats prompting it yourself

    This skill enforces a rigid eligibility matrix and calculation logic that prevents common human errors like double-counting excluded downtime. It ensures every decision follows a standardized financial approval workflow and includes a corrective action plan, which a simple prompt would likely overlook.

    Use cases

    • Verifying if a specific outage triggered an SLA breach for a high-value enterprise account.
    • Calculating partial credits when only a subset of services or regions experienced degraded performance.
    • Evaluating late claim submissions or incidents caused by customer-side configuration errors.
    • Drafting professional claim denials that cite specific exclusions without damaging the customer relationship.

    Known limitations

    Requires manual input of contract terms or evidence if not provided in the context. Does not provide legal advice or handle fraud/chargeback disputes.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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    Creator

    Mariusz Wrzeszczynski
    Mariusz Wrzeszczynski

    109 skills on Agensi

    Frequently Asked Questions

    Popular in Finance, Legal & Accounting