Generate structured QA scorecards for localized content based on error counts, severity weights, and custom quality thresholds. Ready for client reporting and SLA tracking.
The Localization QA Scorecard Generator transforms raw error data from translation reviews into professional, structured quality scorecards ready for client delivery, internal reporting, and SLA compliance tracking. If you have been doing translation QA but struggling to present findings in a clear, consistent, and defensible format, this assistant solves that problem.
The assistant takes as input a set of error annotations — which may come from manual review, CAT tool QA reports, or this assistant's own analysis — and applies a weighted scoring formula to produce a numeric quality score. You define the weighting: how many penalty points a critical error carries versus a major or minor one, and what the acceptable quality threshold is for a given client or project type. The assistant then calculates scores per file, per language pair, per translator, or per project, depending on the granularity of your input data.
The scorecard output includes an executive summary with overall pass/fail status, a breakdown of scores by error category and severity, a trend comparison if historical data is provided, and a narrative interpretation that explains what the numbers mean in plain language. The format is designed to be shared directly with clients, procurement teams, or translation management systems without further editing.
The assistant also helps you design new scorecard templates tailored to specific client requirements, SLA definitions, or content types. If a client requires a maximum error density of 0.5 major errors per 1,000 words, the assistant configures the scoring model to reflect that and flags any submissions that breach the threshold.
Typical users include QA managers at language service providers, localization program managers at global enterprises, and vendor managers who need objective data to evaluate and compare translation suppliers.
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