docx
This Claude Code skill creates, reads, edits, and manipulates Word documents (.docx files) using JavaScript libraries and command-line tools. Use it when users request professional documents with formatting like tables of contents, headings, or images; need to extract or reorganize existing .docx content; or require deliverables such as reports, memos, or letters in Word format. Do not use for PDFs, spreadsheets, or Google Docs.
git clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skills /tmp/docx && cp -r /tmp/docx/skills/docx ~/.claude/skills/docxSKILL.md
# DOCX creation, editing, and analysis
A `.docx` is a ZIP archive of XML files. Choose your approach by task:
| Task | Approach |
|---|---|
| **Create** a new document | Write a `docx` (npm) script — see gotchas below |
| **Edit** an existing document | `unzip` → edit `word/document.xml` → `zip` (docx-js cannot open existing files) |
| **Read** content | `pandoc -t markdown file.docx` |
> Script paths below are relative to this skill's directory.
## Creating with docx-js — gotchas
`docx` is preinstalled — do not run `npm install` first; write the script and `require('docx')` directly. Only if that require fails: `npm install docx`. The model knows the API; these are the footguns:
- **Page size defaults to A4.** For US Letter set `page: { size: { width: 12240, height: 15840 } }` (DXA; 1440 = 1″).
- **Landscape:** pass portrait dimensions and `orientation: PageOrientation.LANDSCAPE` — docx-js swaps width/height internally.
- **Tables need dual widths:** set `columnWidths` on the table AND `width` on every cell, both in `WidthType.DXA` (PERCENTAGE breaks in Google Docs). Column widths must sum to the table width.
- **Table shading:** use `ShadingType.CLEAR`, never `SOLID` (renders black).
- **Lists:** never insert `•` literally; use a `numbering` config with `LevelFormat.BULLET`.
- **`ImageRun` requires `type:`** (`"png"`, `"jpg"`, …).
- **`PageBreak` must be inside a `Paragraph`.**
- **Never use `\n`** — use separate `Paragraph` elements.
- **TOC:** headings must use built-in `HeadingLevel.*`; custom heading styles need `outlineLevel` set or they won't appear.
- **Don't use a table as a horizontal rule** — use a paragraph bottom border instead.
- **Dot-leader / right-aligned-on-same-line:** use `PositionalTab` (`alignment: PositionalTabAlignment.RIGHT`, `leader: PositionalTabLeader.DOT`) inside a `TextRun`, not literal `.` or space padding.
## Verify the output
After writing a `.docx`, render it and look at it:
```bash
python scripts/office/soffice.py --headless --convert-to pdf output.docx
pdftoppm -jpeg -r 100 output.pdf page
ls page-*.jpg # then Read the images
```
`pdftoppm` zero-pads page numbers to the width of the page count (`page-01.jpg`…`page-12.jpg`).
## Editing existing documents
Legacy `.doc` files must be converted first: `python scripts/office/soffice.py --headless --convert-to docx file.doc`.
```bash
unzip -q doc.docx -d unpacked/
find unpacked -type l -delete # strip symlink entries — docx from external parties is untrusted
python scripts/merge_runs.py unpacked/ # coalesce fragmented runs so text is findable
# edit unpacked/word/document.xml in place — do NOT reformat or pretty-print
(cd unpacked && rm -f ../out.docx && zip -Xr ../out.docx .)
python scripts/office/validate.py out.docx --original doc.docx # XSD checks; --auto-repair fixes common issues
# redlining? add --author "<the name you redlined under>" to check every edit is tracked
```
Word splits text across many `<w:r>` runs (revision ids, spell-check markers), so a phrase you can see in the document often doesn't exist as a contiguous string in the XML. `merge_runs.py` merges adjacent identically-formatted runs in `word/document.xml` without changing content or rendering; it also accepts a `.docx` directly (`python scripts/merge_runs.py doc.docx -o merged.docx`).
**Tracked changes:** when redlining, validate with `--author "<the name you redlined under>"` (needs `--original`) — it reports any text you changed without a `<w:ins>`/`<w:del>` around it, which is easy to do by accident and invisible in the accepted view. Wrap runs in `<w:ins>`/`<w:del>` with `w:id`, `w:author`, `w:date` attributes. Inside `<w:del>`, the text element is `<w:delText>`, not `<w:t>`. A deleted paragraph mark (`<w:pPr><w:rPr><w:del w:id=".." w:author=".." w:date=".."/></w:rPr></w:pPr>`) means "merge this paragraph into the next" — so deleting a paragraph outright is that plus a `<w:del>` around every run. The `<w:del/>` must come before the rPr's other children; their order is schema-enforced.
To produce a clean copy with all tracked changes accepted: `python scripts/accept_changes.py in.docx out.docx`.
Accepting a deleted paragraph mark should join that paragraph to the one below it, so a paragraph whose runs are *all* deleted vanishes. Word does this; `accept_changes.py` and `pandoc --track-changes=accept` don't always. Both fail the same way — they strip the deleted text but leave the emptied paragraph behind, which reads as a stray empty bullet when it was auto-numbered:
- `pandoc --track-changes=accept` never joins the paragraphs.
- `accept_changes.py` (LibreOffice) joins them correctly, except when the deleted paragraph is followed by an empty spacer paragraph.
An empty bullet in either view is an artifact of that view, not a defect in the document. Check paragraph deletions in the XML.
## Comments
Comments require six cross-linked files. Use the helper — directory mode when you'll also be editing `document.xml` (saves an unzip/rezip cycle), `.docx`-direct mode otherwise:
```bash
# Against an already-unpacked directory (preferred when also placing markers)
python scripts/comment.py unpacked/ "Fees & expenses cap is too low"
python scripts/comment.py unpacked/ "Agreed" --parent 0
# Against a .docx directly
python scripts/comment.py contract.docx "This cap is too low" -o annotated.docx
```
The script writes `comments.xml`, `commentsExtended.xml`, `commentsIds.xml`, `commentsExtensible.xml`, the relationships, and the content-type overrides. Comment IDs are auto-assigned. It then prints the `<w:commentRangeStart>`/`<w:commentRangeEnd>`/`<w:commentReference>` snippet to add to `word/document.xml` so the comment anchors to specific text — until you place those markers, the comment exists but is not visible.
## Dependencies
`docx` (npm, preinstalled — install only if `require('docx')` fails) · `pandoc` · LibreOffice (`soffice`) · `pdftoppm` (Poppler)
---
*This skill is created and maintained by [AnthropHow to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.
Core Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.
Observe the user's screen via screenpipe, detect repeated research workflows, match them against existing scientific-agent-skills, and draft new skills (or composition recipes that chain existing ones) for the patterns not yet covered. Use when the user asks to analyze their recent work and propose skills based on what they actually do. Requires the screenpipe daemon (https://github.com/screenpipe/screenpipe) running locally on port 3030 — the skill has no other data source and will refuse to run if screenpipe is unreachable. All detection runs locally; only redacted cluster summaries reach the LLM.
Benchling Python SDK and REST API integration for registry entities, inventory, ELN entries, workflows, Benchling Apps, and Data Warehouse queries. Use when automating lab data with benchling-sdk or the v2 API.
Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server. Returns 25+ fields per paper including methods, results, sample sizes, quality scores, and conclusions. Use for literature reviews, evidence synthesis, and finding experimental details not available in abstracts alone.