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translation-files/skills/translation-review/SKILL.md
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---
name: translation-review
description: 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 35 clauses but EN stops after 12 sentences. Signal: CN has quoted speech, poems, or a rhetorical climax absent from EN. Flag as "Missing Content" not "Incomplete."
**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`.
## 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
## Scripts
- `scripts/sweep.py` — Mechanical validation sweep for completed reviews
- `scripts/review_csv.py` — Batch CSV/XLSX translation review