skills: rename dharma-translation→translation, delete mpi-project-conventions, move references
- dharma-translation → translation: stripped conventions, kept only technique - Deleted mpi-project-conventions: all content now in AGENTS.md - References moved: meditation-translation, markdown-to-djot → translation/ translation-pitfalls, proofreading-patterns → translation-review/ - Updated AGENTS.md, readme.dj, memory, pdf skill cross-reference - 7 skills → 6 skills
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@@ -56,7 +56,23 @@ One entry per problem category, not per row. Mention affected row numbers.
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## Workflow B: .dj comparison file review
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Use when input is a `.dj` comparison file (Chinese/English alternating line pairs). Produces `translation-findings.dj` and applies patches.
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Use when input is a `.dj` comparison file (Chinese/English alternating line pairs).
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### Two modes — always clarify which one
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AGENTS.md defines two workflows. Before starting, determine which mode you're in:
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1. **Translation review** (Workflow A in AGENTS.md): agent translated the text.
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Authoritative `target.dj` does not exist yet. Review everything:
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terminology, grammar, formatting, em-dashes, consistency, calques, missing content.
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Produces `translation-findings.dj` and applies patches.
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2. **Proofread** (Workflow B in AGENTS.md): English comes from an existing DOCX
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manuscript. It is authoritative. Only flag manuscript-level mechanical issues:
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typos, double words, numbering mismatches, garbled text, duplicate text.
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Produces `edit-suggestions.dj` ONLY — do NOT apply patches without asking.
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Do NOT flag: terminology choices, djot formatting (em-dashes, italics),
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translation style, calques, word order. These are translation-review concerns.
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### 1. Read the full file
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@@ -173,9 +189,9 @@ Do not run extraction pipelines until scope is clear.
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- **Never delete .dj comparison files** — intentional work artifacts
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- **Verify patches with `cat`** — `read_file` dedup makes it unreliable
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- **Re-read before fixing** — user may have made interim edits
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- **Em-dash drift**: AGENTS.md mandates `—` (Unicode em-dash) → `---` (three hyphens) in English djot. The Chinese source often uses `------` (six hyphens) as its em-dash equivalent; converters or translators may preserve it as a Unicode `—` in the target, which is a convention violation. Run a single find/replace `—` → `---` over the target. Long files typically have 30–50 such instances.
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- **Em-dash drift (translation mode only)**: AGENTS.md mandates `—` (Unicode em-dash) → `---` (three hyphens) in English djot for the translation workflow. When proofreading an existing DOCX manuscript, do NOT flag em-dashes — the manuscript's English is authoritative and this is a formatting concern for the translation workflow. If you're in translation mode and the target has Unicode em-dashes, run a single find/replace `—` → `---`. Long files typically have 30–50 such instances.
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- **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.
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- **Clunky idioms aren't translation errors, they're review items** — a literal calque of a Chinese idiom can read as a typo to a native English reader. Flag these under "Cleanup needed", not "Real errors", and suggest a standard rendering rather than trying to fix in place without confirmation.
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- **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`.
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## References
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# Proofreading: Manuscript vs Typeset
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AGENTS.md defines two workflows: Translation (A) and Proofread (B).
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The workflows below are Proofread mode — English comes from an existing
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manuscript and is authoritative. Only flag mechanical/manuscript-level issues.
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## Two extraction workflows
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### A. Bilingual from DOCX (standard)
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When the DOCX manuscript has both Chinese and English in 1:1 paragraph
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correspondence, generate `bilingual.dj` directly from the DOCX:
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1. `pandoc docx → plain text`
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2. Extract Chinese-English pairs from body
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3. Apply fixes: italicize Sanskrit on first occurrence, fix `N.Letter` → `N. Letter` spacing
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4. Write bilingual.dj
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The DOCX English is the authoritative target text. No PDF needed.
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**Extraction approach**: start by adapting `scripts/gen-bilingual-docx.py`.
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For articles where the body has strict CN→EN→CN→EN alternation, the simple
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extraction in that script (CN line, blank, EN line, blank) works directly.
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**Block-based extraction** (for articles with mixed ordering): when the DOCX has
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sections that order CN content before EN content (CN heading → CN body → EN heading →
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EN body), the simple alternation fails. Use block-based extraction instead:
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1. Tag each non-blank line as CN or EN (via `has_cjk()`)
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2. Join page-break split paragraphs: merge consecutive same-language paragraphs
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only when the first is long (>30 chars), doesn't end with CJK/ASCII terminal
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punctuation (`[。！？：）.?!]$`), and isn't heading-like (starts with
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`^[\dIVX]+[\.\s]` and <60 chars)
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3. Group consecutive same-language items into blocks
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4. Walk blocks: for each CN block, pair with the next EN block via `zip()`.
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`min(len(cn), len(en))` handles translator-introduced paragraph splits.
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**Page-break splits in pandoc plain-text output**: the DOCX→plain conversion
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sometimes splits a Chinese paragraph mid-sentence (e.g. `白居` + `易、苏轼…`).
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These appear as two consecutive CN lines separated by a blank. The join heuristic
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above catches these reliably. For EN text, page-break splits are rare; the heading
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detection (`^[\dIVX]+[\.\s]`, <60 chars) prevents false merges of EN headings
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with following EN body paragraphs.
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The DOCX English is the authoritative target text. No PDF needed.
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### B. Bilingual from PDF (when PDF is the typeset target)
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When the PDF English is the typeset "final" version and should be the target:
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1. Extract DOCX Chinese paragraphs (source)
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2. Extract PDF body text via `pdftotext -layout`
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3. Clean PDF: remove slug lines, headers, page numbers, join hyphenation breaks
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4. Match DOCX English paragraphs against PDF body to find positions
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5. Segment PDF body at matched positions
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6. Write bilingual.dj with Chinese source + PDF English target
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**Pitfalls in PDF extraction:**
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- Consecutive hyphenation breaks (e.g. `thou-` + `sand...al-` + `leviate`) — the join
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loop must be recursive: after joining pair N, check if result still ends with `-`
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and join with line N+2
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- Lines with leading whitespace: use `lstrip()` before checking `n[0].islower()`
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- Drop-cap artifacts: `L iving` → `Living`
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- Trailing section numbers: `...viewpoints. 1)` — the ` 1)` is a PDF section marker
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bleeding into the previous paragraph
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### C. Edit suggestions (edit-suggestions.dj)
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After generating bilingual.dj, scan for issues and write `edit-suggestions.dj`:
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**Format**: follow the original document's section/chapter layout. Group suggestions
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under the chapter headings where the issues occur. Use diff-style `-/+` notation.
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**What to flag:**
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- Garbled Chinese text (merged duplicate edits in source DOCX)
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- Repeated words (`the The`)
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- Chapter numbering mismatches (e.g. `九` ↔ `VIII`)
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- Translator notes in headings (`（善鑫翻，妙一审）`)
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- Missing quotes around dialogue/speech
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## Common source DOCX issues
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- Translator notes in Chinese headings: `（某某翻，某某审）` — delete for publication
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- Merged duplicate edits: cut-paste errors where old+new text appear together
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- `N.Letter` without space: `2.How` → `2. How`
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- `the The` double article
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- **Numbering mismatches**: CN and EN headings sometimes disagree (e.g. CN `3．` vs EN `2.`).
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The TOC usually has the correct number — flag the body heading for correction.
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- **Doubled names**: `岳麓书院岳麓书院` — cut-paste artifacts in Chinese body text.
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- **EN paragraph splits without CN counterpart**: translator sometimes renders one CN
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paragraph as two EN paragraphs. The block-based extractor drops the extra EN paragraph
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(as `min(len_cn, len_en)`). Flag in edit-suggestions so it can be manually merged or
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the CN paragraph can be split.
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## Sanskrit italicization
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On first occurrence in body text, wrap with `*term*`. Track seen terms across
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the full body. Terms: bodhisattva, bodhicitta, samsara, Dharma, karma, nirvana,
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Sangha, sutra, Mahayana, Sravaka, Vinaya, Lamrim, Ksitigarbha, Samantabhadra,
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Chan, Arhatship, Theravada.
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## Proofread scope boundary
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When proofreading a DOCX manuscript:
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- **DO flag**: typos, double words, double punctuation, numbering mismatches,
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garbled text, translator notes, duplicate names, capitalization errors.
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- **Do NOT flag**: em-dash formatting (`—` vs `---`), terminology choices,
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translation style, calques, word order. The manuscript English is authoritative.
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- **Do NOT apply fixes** — write `edit-suggestions.dj` only.
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- If the user asks for translation review separately, write findings to
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`translation-findings.dj`.
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# Translation Pitfalls — MPI Buddhist Texts
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Patterns found in CN→EN translation review. Add to this file as new patterns emerge.
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## Terminology conflation
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### 关爱/关怀 → compassion (WRONG)
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Chinese 关爱 and 关怀 mean "care" or "loving care." They are NOT 慈悲 (compassion / karuṇā).
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Conflating them obscures two distinct Buddhist concepts.
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Check every occurrence of "compassion" in a translation against the source:
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- If source is 关爱/关怀 → "care"
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- If source is 慈悲 → "compassion" (correct)
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- If source is 悬壶济世 → "compassionate mission" (correct — the healing spirit)
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### 生存层面 → making a living (WRONG)
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生存层面 = the existential/survival dimension. Not just earning wages.
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→ "survival-level needs" or "the level of basic existence"
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## Loss of Dharma meaning
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### 生生增上 → continuously elevate our life (INCOMPLETE)
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生生 = life after life (multi-life Buddhist perspective). The single-life rendering
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"continuously elevate our life" loses the Dharma meaning entirely.
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→ "continuously elevate our life, life after life"
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## False implication
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#### 因病返贫 → "back into poverty"
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"返贫" means becoming poor due to illness, not returning to previous poverty. Use "into poverty" or "driven into poverty."
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#### Diacritics: use DB form, not academic Sanskrit
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| Wrong | Right | Source |
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|---|---|---|
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| `Mahāsthāmaprāpta` | `Mahasthamaprapta` | 佛教术语 |
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| `Yogācārabhūmi Śāstra` | `Yogacarabhumi-Sastra` | 经论名 |
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| `Avalokiteśvara` | `Guanyin` | 佛教术语 |
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| `pravāraṇā` | `Pavarana` | BAICKZ |
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Exception: `Kṣitigarbha` — DoT定稿 uses diacritics, so keep them.
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When in doubt, search the DB and follow the highest-priority source. See dharma-translation skill `references/diacritics-convention.md`.
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返贫 = become poor (from a non-poor state) due to medical costs. "Back" implies
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the person was previously poor — not necessarily true. This is about medical bankruptcy.
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→ "into poverty" or "fall into poverty" (no "back")
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## DoT定稿 term drift
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### 念死 → recollection of death (WRONG per DoT定稿)
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DoT定稿 has "Cultivating mindfulness of death" / 佛教术语 has "contemplating the
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impermanence of death". The established term is "mindfulness of death", not
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"recollection of death." → "mindfulness of death" / "death-mindfulness"
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### 三级修学 → Three-Level Study Program (WRONG per DoT定稿)
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DoT定稿 has "Three-Stage Practice." → "Three-Stage Practice"
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### 下士道/中士道/上士道
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DoT定稿: "Path for Persons of Small/Medium/Great Capacity" — not "path of the
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initial/middle/great scope."
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### 观音菩萨 → Avalokiteśvara (AVOID in MPI translations)
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佛教术语 has "Guanshiyin/Guanyin Bodhisattva." Use "Guanyin Bodhisattva."
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## Workflow pitfall
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### Translating before consulting terms DB
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Always search key terms BEFORE translating. The dharma-translation skill says to do
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this, but it's easy to skip. Use the CLI: `/home/user/documents/mpi/terms-search/search.py <query>`.
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Prioritize DoT定稿 > 内部特色词 > 佛教术语 > 经论名.
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