Translation QA Checker

Review translated content for accuracy, tone consistency, and terminology alignment — catching errors that automated translation tools miss.

translationqalocalizationmultilingual

Translation QA Checker

Machine translation has gotten remarkably good at producing fluent-sounding text. The problem is that fluent and accurate aren’t the same thing. A sentence can read naturally in French while subtly changing the meaning of the original English, using the wrong register for a B2B audience, or applying a term that’s standard in France but confusing in Quebec. This skill catches those gaps before translated content goes live.

TL;DR

Paste in a source text and its translation (or provide a bilingual document). The skill compares them across four dimensions — semantic accuracy, tone and register, terminology consistency, and cultural appropriateness — and returns a structured QA report with flagged segments and suggested corrections. No external API access required; everything runs on the text you provide.

What it does

Translation QA is more nuanced than spell-checking. This skill evaluates translations across dimensions that automated tools typically miss:

  • Semantic accuracy review — Compares source and target segments sentence by sentence, flagging cases where meaning has shifted, been omitted, or been added without basis in the source. Particularly useful for catching “hallucinated” additions that machine translation sometimes introduces.
  • Tone and register consistency — Checks whether the translation maintains the formality level of the source. A casual, conversational brand voice in English should not become stiff and formal in German. The skill flags register mismatches and suggests alternatives that preserve the intended tone.
  • Terminology consistency audit — If you provide a glossary or termbase, the skill verifies that approved terms are used consistently throughout the document. It flags instances where a translator used a synonym instead of the approved term, which matters for regulated industries and brand consistency.
  • Cultural adaptation assessment — Identifies idioms, metaphors, humor, and cultural references in the source that may not translate directly, and evaluates whether the translator handled them appropriately (adapted, explained, or replaced with a local equivalent).
  • Numerical and formatting verification — Checks that dates, currencies, measurements, phone number formats, and address structures have been correctly adapted to the target locale — not just translated but localized.
  • Segment-level error classification — Categorizes each flagged issue by severity (critical, major, minor) and error type (accuracy, fluency, terminology, style, locale convention), following the MQM (Multidimensional Quality Metrics) framework used by professional localization teams.

Best for

  • Localization teams reviewing output from machine translation engines (DeepL, Google Translate, Amazon Translate) before post-editing or publication.
  • Multilingual content operations at companies publishing in 5+ languages, where human review of every segment isn’t feasible but quality standards still need to be maintained.
  • Document review workflows for legal, medical, or compliance content where translation errors carry real risk — the skill’s severity classification helps prioritize which segments need human expert review.

This skill works best as a first-pass filter, not a replacement for human bilingual review on high-stakes content. Use it to triage a 10,000-word document so your human reviewers focus on the 200 words that actually need attention.

How to use (example)

Scenario: Your SaaS company has just had its onboarding email sequence translated from English to Spanish (Latin American). You need to QA the translation before the campaign goes live next week.

Input

Source language: English (en-US)
Target language: Spanish (es-419, Latin American)
Document type: Marketing email sequence (5 emails, ~1,200 words total)
Brand voice: Friendly, conversational, encouraging — avoid formal "usted" register
Glossary: [attached: approved-terms-es.csv]
  - "dashboard" → "panel de control" (not "tablero")
  - "onboarding" → "incorporación" (not "bienvenida")
  - "free trial" → "prueba gratuita" (not "período de prueba")
QA level: Standard (flag major and critical issues; note minor issues separately)
Output format: Segment-by-segment report with severity ratings and suggested corrections

What the skill produces (excerpt)

TRANSLATION QA REPORT
Document: Onboarding Email Sequence (en-US → es-419)
Segments reviewed: 87
Issues found: 12 (2 critical, 5 major, 5 minor)

---
CRITICAL ISSUES (require correction before publication)

Segment 14
Source: "Your free trial expires in 7 days — upgrade now to keep your data."
Translation: "Su período de prueba vence en 7 días — actualice ahora para conservar sus datos."
Issue: Terminology — "período de prueba" used instead of approved term "prueba gratuita"
Also: "Su" (formal usted register) inconsistent with brand voice guideline
Suggested correction: "Tu prueba gratuita vence en 7 días — actualiza ahora para conservar tus datos."

Segment 31
Source: "Hit the ground running with our quick-start guide."
Translation: "Golpee el suelo corriendo con nuestra guía de inicio rápido."
Issue: Idiom translated literally — "golpear el suelo corriendo" is not a Spanish expression and reads as nonsense
Suggested correction: "Empieza con el pie derecho con nuestra guía de inicio rápido." (equivalent idiom)

---
MAJOR ISSUES (should be corrected; may affect comprehension or brand perception)

Segment 8
Source: "You're all set!"
Translation: "¡Está todo listo!"
Issue: Register — impersonal construction where brand voice calls for direct address
Suggested correction: "¡Ya estás listo!" or "¡Todo listo!"

[...5 more major issues...]

MINOR ISSUES (style preferences; correct if time allows)
[...5 items with suggestions...]

Variations

  • Glossary-free mode: If you don’t have an approved termbase, the skill will flag terminology inconsistencies within the document itself (e.g., the same concept translated three different ways across the document).
  • Batch mode: Provide multiple documents in a ZIP or as a list of file paths. The skill processes each one and returns a combined report with per-document summaries.
  • Back-translation check: Add include_back_translation: yes to get a literal English rendering of each flagged segment, which helps non-bilingual stakeholders understand what the translation actually says.

Permissions & Risks

Required permissions: None — the skill operates entirely on text you provide
Risk level: Low

No external calls are made. Your source and translated content stays within the session context. The main risk is over-correction of valid regional variants: the skill may flag a term that’s correct for one Spanish-speaking country as an error because it doesn’t match a different regional standard. Always specify the target locale precisely (e.g., es-419 for Latin American Spanish, es-ES for Castilian Spanish) to minimize false positives.

A second risk: technical terminology in specialized domains. The skill has broad language knowledge but may not recognize highly specialized terms in fields like pharmaceutical regulation, patent law, or semiconductor manufacturing. For those domains, supplement with a domain-specific glossary and have a subject matter expert review critical terminology flags.

Troubleshooting

  1. Too many false positives — valid translations being flagged as errors
    The most common cause is an underspecified locale. Change es to es-MX or es-AR and re-run. Also check whether your glossary contains terms from a different regional variant than your target audience.

  2. Skill misses obvious errors in a specific language pair
    Some language pairs have stronger coverage than others. For less common pairs (e.g., English to Catalan, or Japanese to Thai), provide more context about the document type and audience, and treat the output as a starting point for human review rather than a final QA pass.

  3. Cultural adaptation flags seem overly conservative
    The skill defaults to flagging any idiom or cultural reference that doesn’t have a direct equivalent. If your translation strategy is to keep source idioms and let context carry the meaning, add adaptation_strategy: retain_source_idioms to suppress those flags.

  4. Terminology audit misses inconsistencies
    This happens when the same concept appears in multiple surface forms in your glossary (e.g., “free trial,” “trial period,” “trial account” all mapped to different approved terms). Consolidate your glossary so each concept has one canonical source term before running the audit.

  5. Report is too long to act on efficiently
    Use qa_level: critical_only to get a focused report with only the issues that must be fixed before publication. Run a full report separately for the post-publication improvement backlog.

  6. Numerical formatting errors not being caught
    Specify the target locale’s formatting conventions explicitly if they differ from the default: date_format: DD/MM/YYYY, currency_symbol: position: after, decimal_separator: comma. The skill uses locale defaults otherwise, which may not match your style guide.

Alternatives

  • Smartling QA — Enterprise localization platform with built-in QA checks integrated into the translation workflow. Better for teams already using Smartling as their TMS; overkill if you just need occasional QA on external translations.
  • Memsource QA checks (now Phrase) — Automated QA rules built into the CAT tool environment. Excellent for in-workflow checking but requires translators to be working inside Memsource; doesn’t help with reviewing translations delivered as Word documents or plain text.
  • Human bilingual review — A professional translator or bilingual editor reviewing the translation against the source. Highest accuracy, especially for nuanced content. Use this skill to triage first so human reviewers spend their time on segments that actually need attention.

Skills:

  • Content Brief — Build multilingual content briefs that specify tone and terminology requirements upfront, reducing QA issues downstream
  • KB Builder — Maintain a multilingual knowledge base with consistent terminology across languages
  • Support Macros — QA translated support reply templates before deploying them to multilingual helpdesk queues

Guides:

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