Reports#
Reports give you visibility into how your localization engines are performing — translation volume, token usage, locale coverage, glossary health, and codebase change rates. All reports are scoped to your organization and update automatically as requests flow through the engine.
Available reports#
| Report | What it measures |
|---|---|
| Word Generations | Words translated per day |
| Token Consumption | Input and output tokens used per day |
| Top Locales | Which locales consume the most resources |
| Glossary Coverage | How many glossary terms exist per locale |
| Change Rate | Localization file changes in GitHub by locale |
Word Generations#
Tracks the total word count processed by the localization engine, aggregated by day. Use this to understand translation volume trends and plan capacity.
Filters: engine, period (month), source locale, target locale
The chart displays one bar per day for the selected month. Days with no translation activity show zero.
Token Consumption#
Monitors LLM token usage broken down into input tokens and output tokens, aggregated by day. Token consumption directly reflects cost — use this report to identify cost spikes and compare efficiency across engines or locale pairs.
Filters: engine, period (month), source locale, target locale
Input vs. output tokens
Input tokens include the system prompt, glossary, brand voice, instructions, and the source text. Output tokens are the translated result. A high input-to-output ratio may indicate that the engine's context (glossary, instructions) is large relative to the translated content.
Top Locales#
Ranks locales by resource consumption — helping you identify which languages drive the most translation volume and cost. You can view rankings by source locale or target locale, and measure by input tokens, output tokens, or word count.
Filters: engine, period (month), locale type (source or target), metric (input tokens, output tokens, or word count)
This report answers questions like: "Which target locale uses the most tokens?" or "Which source language generates the most words?"
Glossary Coverage#
Shows how many glossary items exist per locale across your engines. Unlike other reports, this is a current snapshot — not time-series data — reflecting the present state of your glossary configuration.
Filters: engine, locale type (source or target)
Use this to identify gaps: if your engine translates into 12 locales but only 3 have glossary coverage, the uncovered locales rely entirely on the model's judgment for terminology.
Change Rate#
Tracks the rate of localization file changes in your connected GitHub repositories, broken down by locale and day. This report requires an active GitHub integration — you'll be prompted to connect GitHub if it isn't set up.
Filters: period (month), repository, locale
The change rate report helps answer: "How actively is each locale being updated?" and "Which repositories generate the most localization changes?"
Timezone support
Date grouping respects your organization's configured timezone. A commit at 23:30 UTC appears on the correct local date, not shifted to the next day.
Filtering and periods#
All time-based reports operate on monthly periods. The default is the current month. Filters are preserved in the URL, so filtered views are shareable and bookmarkable.
Common filters across reports:
| Filter | Available in | Description |
|---|---|---|
| Engine | Word Gen, Token, Top Locales, Glossary | Narrow to a specific engine or view all |
| Period | Word Gen, Token, Top Locales, Change Rate | Select month (YYYY-MM) |
| Source locale | Word Gen, Token | Filter by source language |
| Target locale | Word Gen, Token | Filter by target language |
| Repository | Change Rate | Filter by GitHub repo |
Quality scoring reports#
Translation quality metrics — pass rates, percentage scores, and per-locale-pair breakdowns — are covered under Scorers. The scoring reports provide a complementary view: while these reports track volume and cost, scorer reports track quality.