Run a quality benchmark of the /translate skill by selecting stratified test keys, capturing ground truth, translating, judging with sub-agents, and compiling a regression report. Invoke with /benchmark-translate.
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name
benchmark-translate
description
Run a quality benchmark of the /translate skill by selecting stratified test keys, capturing ground truth, translating, judging with sub-agents, and compiling a regression report. Invoke with /benchmark-translate.
Measures the quality of the /translate skill by comparing its output against existing human translations. Uses stratified key selection with a fixed/rotating split, LLM judges, and programmatic validation to produce a comprehensive quality report with regression tracking across all 9 supported locales.
Data Artifacts
All benchmark data lives in scripts/translations/benchmark/ (gitignored):
File
Purpose
testKeys.json
Selected test keys with categories and fixed flag
coreKeys.json
Persistent core key set (stable across runs)
ground-truth.json
Captured human translations before removal
report.json
Latest benchmark report (becomes baseline on next run)
Selects N keys (default 150) stratified across 6 categories: glossary-term, financial-error, single-word, interpolation, defi-jargon, general. Validates all selected keys exist in en + all 9 locales.
Fixed/rotating split:
--core N (default 100): Number of fixed core keys for stable regression tracking
--count N (default 150): Total keys (core + rotating)
If coreKeys.json exists: loads it, validates keys still exist in all locales, tops up if needed
If coreKeys.json doesn't exist: selects core keys via stratified sampling and saves them
Remaining keys (default 50) are randomly selected as rotating keys from the non-core pool
Each entry in testKeys.json has "fixed": true (core) or "fixed": false (rotating)
If report.json exists from a previous run, copies it to baseline.json
Reads testKeys.json, captures ground truth translations for all 9 locales
Writes ground-truth.json
Removes test keys from locale files so /translate can regenerate them
Step 3: Translate
Invoke the /translate skill using the Skill tool. This regenerates the removed keys through the full translate-review-refine pipeline.
Step 4: Judge (Sub-Agents)
Launch 9 sub-agents in 3 waves of 3 (matching /translate's wave structure) using the Task tool. Each sub-agent receives the locale info, all key triplets, and glossary terms.
You are an expert multilingual localization quality assessor for a cryptocurrency/DeFi application.
Rate translations from English into {LANGUAGE_NAME} on a 1-5 scale.
1 = Wrong/misleading meaning
2 = Significant issues (wrong register, missing nuance)
3 = Acceptable but could be more natural
4 = Good, natural, accurate
5 = Excellent, indistinguishable from professional native translation
Check: meaning preservation, naturalness, register ({REGISTER}), UI conciseness,
glossary compliance (these stay English: {NEVER_TRANSLATE_TERMS}),
placeholder integrity (%{...} preserved), DeFi terminology conventions.
Rate each translation INDEPENDENTLY. Community translations can contain errors.
Input: JSON array of {key, english, human, skill}
{ITEMS_JSON}
Output: Return ONLY a JSON array of objects with these exact fields:
{key, humanScore, skillScore, humanJustification, skillJustification, preferenceNote}
Scores must be integers 1-5. Justifications should be 1-2 sentences. preferenceNote should say which is better and why, or "tie" if equal.
Read the current (post-translate) src/assets/translations/{locale}/main.json
For each test key, build: { key: dottedPath, english: groundTruth.english[key], human: groundTruth.groundTruth[locale][key], skill: getValueFromLocaleFile(key) }
Getting never-translate terms: Read src/assets/translations/glossary.json, collect all keys where value is null (excluding _meta).
Each sub-agent must write its output to /tmp/{locale}-judge-scores.json. Parse the JSON array from the sub-agent's response and write it to that path.
Loads judge scores from /tmp/{locale}-judge-scores.json, runs programmatic validation (including Cyrillic script check for ru/uk), computes summary stats, and writes scripts/translations/benchmark/report.json. If baseline.json exists, includes regression deltas. Report includes coreSummary and rotatingSummary alongside the overall summary.
