tq-writer

name	tq-writer
description	Update translation questions to align with current ULT/UST. Use when asked to update translation questions or generate TQ for a chapter.

Translation Question Writer

Update existing Translation Questions (TQs) to align with current ULT/UST texts. A preparation script handles all data extraction, then the AI reviews each chapter's TQs against the source texts and produces updated TSV.

Prerequisites

source .env  # provides $DOOR43_REPOS_PATH

• en_tq repo cloned at $DOOR43_REPOS_PATH/en_tq
• ULT/UST available (output/ files, repo clones, or fetched from Door43)

Workflow

Step 1: Ensure en_tq Clone

TQ_REPO="$DOOR43_REPOS_PATH/en_tq"
if [ ! -d "$TQ_REPO" ]; then
  git clone [e-mail]:unfoldingWord/en_tq.git "$TQ_REPO"
fi
# Pull latest if stale (more than a day old)
cd "$TQ_REPO" && git pull origin master

Step 2: Run Preparation Script

Use mcp__workspace-tools__prepare_tq with book="PSA", chapter=150, output="/tmp/claude/prepared_tq.json" for a single chapter. For a whole book, omit chapter and pass wholeBook=true.

The tool auto-detects ULT/UST from:

1. output/AI-ULT/ and output/AI-UST/ (AI-generated files)
2. Repo clones at $DOOR43_REPOS_PATH/en_ult and en_ust
3. Door43 fetch as fallback

Override with ultPath or ustPath if needed.

Step 3: Read Guidelines

Read reference/tq-guidelines.md for the TQ update rules.

Step 4: Review and Update TQs

Read /tmp/claude/prepared_tq.json. For each chapter:

1. Read the existing TQ rows from tq_rows_by_chapter
2. Read the ULT text from ult_by_verse and UST text from ust_by_verse
3. Compare each TQ row's question and response against the current ULT and UST; default to ULT language for questions and responses; fall back to UST language only when the ULT rendering is metaphorical, uses Hebrew idioms, or is otherwise not plain/accessible English — use the UST's non-figurative wording for those cases
4. Update rows where needed following the guidelines

Output format: Write updated TSV rows to the output file, one chapter at a time. Include the header row. Use the same 7-column format:

Reference	ID	Tags	Quote	Occurrence	Question	Response

Rules for AI updates:

• Return the full set of rows for the chapter (not just changed ones)
• Preserve existing IDs -- do not change the ID column
• ID uniqueness is mandatory: Before emitting each row, check its ID against every ID already written in the current output (across all chapters processed so far in this session). If a collision is detected — including between a single-verse row and a multi-verse range row that covers the same verse — assign a new unique 4-char ID ([a-z][a-z0-9]{3}) to the colliding row and confirm the replacement ID is not already in use. Never emit two rows with the same ID.
• Preserve Tags, Quote, and Occurrence columns as-is (usually empty)
• Only modify Reference (if the ULT/UST content has genuinely moved to a different verse), Question, and Response
• Multi-verse reference spans: if the source row carries a range reference (e.g., 18:9-10, 24:1-2), copy it exactly into the output — do NOT collapse it to only the first verse
• Follow tq-guidelines.md for content rules (third person, present tense, ESL level, etc.)
• If a row already matches the current ULT/UST, leave it unchanged

Write the result as a TSV file to output/tq/{BOOK}/{BOOK}-{CHAPTER}.tsv using exactly 3-digit chapter padding (e.g., PSA/PSA-007.tsv, PSA/PSA-023.tsv, PSA/PSA-150.tsv), or output/tq/{BOOK}/{BOOK}.tsv for whole-book processing.

Step 5: Post-Process Quotes

Use mcp__workspace-tools__curly_quotes with input="output/tq/PSA/PSA-006.tsv", inPlace=true.

Step 6: Verify Output

Use mcp__workspace-tools__verify_tq with tsvFile="output/tq/PSA/PSA-006.tsv", inputJson="/tmp/claude/prepared_tq.json".

Step 6.5: Duplicate ID Check

After writing all chapter files, scan the full output for duplicate IDs before proceeding to insertion. Use mcp__workspace-tools__check_tn_quality with tsvFile pointing to the output TSV and look for any id_duplicate findings. For multi-chapter or whole-book runs, check each chapter file in sequence and maintain a cross-chapter seen-ID set.

If check_tn_quality is unavailable for TQ files, perform the check manually: read all output rows, collect the ID column, and report any ID that appears more than once. Fix any duplicate by replacing the later-occurring ID with a freshly generated unique value before proceeding to insertion.

Why this step exists: verify_tq (Step 6) does not detect duplicate IDs. Duplicates break downstream processing software (merge/delete matching fails). This explicit check is the safety net against AI sessions that generate the same random ID for two different verse rows (e.g., one for verse 53:2 and one for the range 53:2-3).

Step 7: Insertion (when ready)

Use door43-push-cli.js with --type tn (TQ uses the same insertion path as TN). For interactive dry-run preview, use the repo-insert skill's Step 2 guidance.

Input Format

TQ TSV (7 columns with header):

Reference	ID	Tags	Quote	Occurrence	Question	Response
150:1	u3co				Where should everyone praise God?	Everyone should praise God in his sanctuary and the mighty heavens.

Output Format

Same 7-column TSV with updated Question and Response content:

Reference	ID	Tags	Quote	Occurrence	Question	Response
150:1	u3co				Where should people praise God?	People should praise God in his holy place and in the mighty heavens.