translation-files/skills/translation-review/SKILL.md

name, description

name	description
translation-review	Review Chinese-English translations for quality issues - terminology, grammar, consistency, formatting. Two workflows - CSV/XLSX batch review (write .dj suggestions) and .dj comparison line-by-line review (surgical patching).

Translation Review

Two workflows, used depending on input format.

Workflow A: CSV/XLSX batch review

Use when input is a CSV/XLSX with Chinese/English columns. Produces an edit-suggestions.dj file.

1. Get the data into CSV

If XLSX, export to CSV (or use openpyxl). CSV is faster.

2. Read the full file

Use read_file with offsets for complete coverage. Don't sample.

3. Write a systematic analysis script

Write to /tmp/script.py, run with python3 /tmp/script.py. No heredocs or -c. The script should:

• Parse CSV with csv.DictReader
• Apply detection rules per category
• Collect issues: row number, CN text, EN text, problem, suggested fix
• Group/deduplicate identical issues

Common detection categories:

• Buddhist terminology: 正念→mindfulness (not "righteous thoughts"), 布施→generosity (not "alms")
• Identity terms: 学士/修士/胜士/智士 are practice stages, not titles
• Literal machine translations: "hard drive" for 硬盘 (endurance)
• 四摄法 terms: 同事→"acting in harmony", 爱语→"kind speech"
• Grammar: subject-verb agreement, unbalanced quotes
• Typos/formatting: Chinese punctuation in English, "IOS"→"iOS"
• Inconsistency: same CN term translated differently across rows

4. Write edit-suggestions.dj

Format:

# 1

original: <Chinese text or key term>
translated: <current English>

<Explanation and suggested fix.>

# 2
...

One entry per problem category, not per row. Mention affected row numbers.

Workflow B: .dj comparison file review

Use when input is a .dj comparison file (Chinese/English alternating line pairs).

Two modes — always clarify which one

AGENTS.md defines two workflows. Before starting, determine which mode you're in:

1. Translation review (Workflow A in AGENTS.md): agent translated the text. Authoritative target.dj does not exist yet. Review everything: terminology, grammar, formatting, consistency, calques, missing content. Produces translation-findings.dj and applies patches.

2. Proofread (Workflow B in AGENTS.md): English comes from an existing DOCX manuscript. It is authoritative. Only flag manuscript-level mechanical issues: typos, double words, numbering mismatches, garbled text, duplicate text. Produces edit-suggestions.dj ONLY — do NOT apply patches without asking. Do NOT flag: terminology choices, djot formatting, translation style, calques, word order. These are translation-review concerns.

1. Read the full file

Use read_file with offset and limit for full coverage of large files (this session had 322 lines, 93KB). For files >200 lines, paginate explicitly rather than reading the whole thing at once.

If you have already read part of the file with read_file earlier in the session, use terminal: cat (or sed -n 'A,Bp') to get an un-deduped view of the rest. read_file deduplicates within a session.

2. Scan for problems — three passes, in order

The review is best done in three distinct passes, each catching a different category of error. Don't try to catch everything in one scan.

Pass 1 — terminology + consistency + line count (fast, mechanical):

• Line count: source and target must match exactly. Mismatch means paragraphs were dropped, merged, or split.
• Same CN term translated differently across the file (e.g. 人生佛教/人间佛教 conflation, 恨→resentment, 修行/修学)
• Buddhist terminology against the MPI terms DB (see terms-db-alignment below)
• Mistranslation of key terms, wrong proper names, garbled text
• Mid-paragraph truncation: CN covers 3–5 clauses but EN stops after 1–2 sentences. Signal: CN has quoted speech, poems, or a rhetorical climax absent from EN. Flag as "Missing Content" not "Incomplete."
• Use references/common-issues-taxonomy.md as a structured checklist for accuracy issues

Pass 2 — mechanical/formatting (also mechanical, but easy to skip):

• TOC format: AGENTS.md says TOC must be plain bullet list, no link targets. Strip [I. Heading](#...) markdown links if present.
• Double words, double punctuation, capitalisation typos, processing artifacts, stray spacing in Chinese text
• Numbering mismatches between CN and EN headings
• Redundant English calques: when the target mirrors a Chinese grammar pattern literally, it can read as a typo (e.g. "mind of death-mindfulness" for 念死之心 — should be "mindfulness of death"). Clunky idioms: 一念之差 → "a single thought of difference" is unidiomatic. Standard renderings exist (e.g. "a single errant thought," "a moment's carelessness," or rephrase as "a single thought can make all the difference").

Pass 3 — flow/tonal/calques (read the whole English as prose):

• Re-read the full English target. Does it hang together as prose, or does it read as "translationese"?
• Dramatic verbs that are calques of Chinese: "draw forth," "into full play," "shoulder," "look to with hope." See references/translation-pitfalls.md for the full calque checklist.
• Subject-shift calques: English substitutes a concrete agent (practitioners, people) for an abstract system noun (Buddhism, religion) — see pitfalls.
• Factual inconsistencies across paired descriptions of the same person/place/thing.
• Tonal coherence inside parallel lists: verb choice should be identical across First/Second/Third items.
• Intensifier drift: same intensifier ("profoundly important") used 3+ times in one section reads as over-translation.
• The user may explicitly request this pass ("are the words together nicely?", "does it read well?"). Treat such prompts as a signal to do the full re-read, not just spot-check.

Terms database drift (cross-cutting — apply during Pass 1):

• Cross-reference glossary terms against the MPI terms database
• CLI preferred: python3 $MPI_PROJECT_ROOT/terms-search/search.py <query>. For a review, batch many queries in one execute_code script (subprocess loop) — one terminal call per term is slow and noisy.
• Source priority: DoT定稿 > 内部特色词 > 佛教术语 > 经论名
• Fix both glossary comments AND body text
• See references/terms-db-alignment.md for batch-lookup patterns

3. Dump findings to translation-findings.dj

Finding N — Title (line numbers)
  Chinese: ...
  English: ...
  Issue: description

4. Apply fixes with patch

Surgical string replacement. Verify every patch with cat — never rely on read_file (session dedup).

5. Add inline translation notes to bilingual.dj

After findings are written, insert djot comments ({% ... %}) into bilingual.dj after translation pairs to document non-obvious translation decisions. This serves as a durable reference for future editors and bilingual readers.

What to annotate:

• Terminology choices: why a particular rendering was chosen (e.g. 人生佛教 → "Buddhism for Human Life" vs "Humanistic Buddhism")
• Cultural bridges: how an idiom or reference was adapted for English readers (e.g. 天龙八部 → expanded to "devas, nāgas, and the rest of the eight classes of beings")
• Structural decisions: heading patterns, name handling, parallelism preservation
• Sanskrit handling: which terms get diacritics, which get glosses, why

Format:

source line
target line
{% explanation of translation choice %}
(blank)

The comment sits on its own line between the target line and the blank separator. Use execute_code to insert comments programmatically — key by source line number (1-indexed), build new file line by line. Verify with head/tail.

Do NOT annotate literal/obvious translations (names, dates, simple connectives). Aim for ~1 comment per significant pair.

6. Final sweep

Run python3 scripts/sweep.py <source.dj> <target.dj> [--stale term1,term2] [--new term1,term2]. This runs all mechanical checks in one call: line parity, heading parity, Unicode em/en-dashes, Markdown bold, Chinese punctuation, TOC link artifacts, unbalanced quotes, and stale/new term assertions. Run even when no content patches were needed — it serves as final validation.

Buddhist terminology reference

See references/buddhist-terminology.md for Chinese-English term mappings and common pitfalls.

Workflow C: Typeset proofread (DOCX manuscript vs PDF layout)

Use when the user gives a manuscript DOCX and a typeset PDF and asks to proofread. Goal: catch typesetting errors (missing text, typos, wrong special characters, bad line breaks), not translation quality.

0. Clarify scope FIRST

Before any extraction: ask what they want checked. "Proofread" can mean:

• Text accuracy (missing/doubled words, typos introduced by typesetter)
• Special characters (quotes, dashes, ellipses)
• Formatting (page numbers, headers, TOC layout)
• All of the above

Do not run extraction pipelines until scope is clear.

1. Extract text

• DOCX → plain: pandoc file.docx -f docx -t plain --wrap=none
• PDF → plain: pdftotext -layout file.pdf (preserves positional info)

2. Clean PDF artifacts

• Strip InDesign slug lines, page headers, page numbers
• Join hyphenated line breaks (line ending - + next line starting lowercase)
• Fix drop-cap artifacts (e.g. L iving → Living)

3. Compare

• Extract English paragraphs from DOCX (skip Chinese lines, match blank-line pattern)
• Check each DOCX paragraph exists as substring in PDF body text
• Flag paragraphs not found; investigate each (may be heading renumbering, not missing)

Pitfalls specific to this workflow

• PDF paragraph joining is lossy — page breaks split paragraphs. Don't expect perfect paragraph matching; check content coverage, not paragraph identity.
• Heading numbering differs — DOCX has 1., (1); PDF has I, 1). Ignore heading-only differences.
• InDesign PDFs insert extra spaces around drop caps and special characters. Normalize multi-space to single space before comparison.

Pitfalls

• Clarify scope before diving into extraction pipelines — if the user says "proofread this" or "校对这篇文章", ask what specifically they want checked before running pandoc/pdftotext. Getting interrupted mid-pipeline wastes context.
• Don't use heredocs or -c — write to /tmp/script.py first
• Deduplicate aggressively — group by problem type, not per-row
• Buddhist terminology is technical — don't guess. When uncertain, flag for review
• Never delete .dj comparison files — intentional work artifacts
• Verify patches with cat — read_file dedup makes it unreliable
• Re-read before fixing — user may have made interim edits
• Batch terminology lookups — when checking many terms against the terms DB, run them in one execute_code script that loops over a query list and calls search.py via subprocess.run. One terminal call per term floods the context with repetitive output.
• Proofread ≠ translation review — when the user says "校对" or "proofread" and the input is a DOCX manuscript with existing English, you are in proofread mode. Do NOT flag translation quality, terminology, or djot formatting. Do NOT apply patches to bilingual.dj unless asked. Write edit-suggestions.dj with manuscript-level issues only. If the user later asks for translation review of the same article, write findings to a separate translation-findings.dj.

Human Review Protocol (审议)

When giving feedback to human translators — whether in a review team or as an AI assistant flagging issues — follow the Oriental Translation Workshop protocol. See references/deliberation-protocol.md for full guidance.

Key points:

• Rejoice first (随喜): affirm what works before flagging issues
• Three-tier issues: Level 1 (spelling/grammar/format) — fix directly. Level 2 (omission/mistranslation/wordiness) — suggest or fix with tracked changes. Level 3 (citation versions / marginal wording) — discuss with translator
• Tone: questions, not commands; collaborative inquiry, not correction
• Address translator as 菩萨 (Bodhisattva) — respectful peer

Common Issues Taxonomy

Use references/common-issues-taxonomy.md as a structured checklist when reviewing. Categories:

• Accuracy: omission, mistranslation (over-free, over-literal, misunderstanding, wrong word choice), overtranslation, terminology errors
• Readability: redundancy (long sentences, passive voice, nominalization), poor structure (top-heavy sentences), wrong register, weak transitions

References

• references/buddhist-terminology.md — Chinese-English Buddhist term mappings and pitfalls
• references/terms-db-alignment.md — Batch-aligning glossary terms against the MPI terms database
• references/translation-pitfalls.md — Recurring CN→EN mistranslation patterns (关爱→compassion, 生生增上, etc.)
• references/proofreading-patterns.md — DOCX/PDF extraction techniques, block-based pairing, common manuscript issues
• references/deliberation-protocol.md — Oriental Translation Workshop review protocol: tiers, rejoicing, tone
• references/common-issues-taxonomy.md — Structured taxonomy of accuracy and readability issues with examples

Scripts

• scripts/sweep.py — Mechanical validation sweep for completed reviews
• scripts/review_csv.py — Batch CSV/XLSX translation review