agentleFS
Sign inStart free
rakaarwakyrakaarwaky/agents-arwaky/skills/office/docx/SKILL.md

docx

Skill0 starsChanged 4 days agoMITView on GitHub

Create, read, edit, template, and review Word .docx files with python-docx CLIs: text, styles, tables, images, {{token}} templates, tracked changes, comments, TOC, and page-number fields.

194 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use Video Generation, VLM and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • huang-x-hSkill

    Video Generation

    Implement AI-powered video generation capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to generate videos from text prompts or images, create video content programmatically, or build applications that produce video outputs. Supports asynchronous task management with status polling and result retrieval.

    Also in 6 projects that use this

  • huang-x-hSkill

    VLM

    Implement vision-based AI chat capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to analyze images, describe visual content, or create applications that combine image understanding with conversational AI. Supports image URLs and base64 encoded images for multimodal interactions.

    Also in 6 projects that use this

  • dav-niu474Skill

    gift-evaluator

    The PRIMARY tool for Spring Festival gift analysis and social interaction generation. Use this skill when users upload photos of gifts (alcohol, tea, supplements, etc.) to inquire about their value, authenticity, or how to respond socially. Integrates visual perception, market valuation, and HTML card generation.

    Also in 5 projects that use this

  • dav-niu474Skill

    Podcast Generate

    Generate podcast episodes from user-provided content or by searching the web for specified topics. If user uploads a text file/article, creates a dual-host dialogue podcast (or single-host upon request). If no content is provided, searches the web for information about the user-specified topic and generates a podcast. Duration scales with content size (3-20 minutes, ~240 chars/min). Uses z-ai-web-dev-sdk for LLM script generation and TTS audio synthesis. Outputs both a podcast script (Markdown) and a complete audio file (WAV).

    Also in 5 projects that use this

  • Liang-MHSkill

    stock_analysis

    获取 A 股、基金和港股的实时行情和技术分析数据

    Also in 5 projects that use this

  • SeifBenayedSkill

    file-reading

    Use this skill when a file has been uploaded but its content is NOT in your context — only its path at /mnt/user-data/uploads/ is listed in an uploaded_files block. This skill is a router: it tells you which tool to use for each file type (pdf, docx, xlsx, csv, json, images, archives, ebooks) so you read the right amount the right way instead of blindly running cat on a binary. Triggers: any mention of /mnt/user-data/uploads/, an uploaded_files section, a file_path tag, or a user asking about an uploaded file you have not yet read. Do NOT use this skill if the file content is already visible in your context inside a documents block — you already have it.

    Also in 5 projects that use this

  • +1 more from huang-x-h
  • +5 more from dav-niu474

The file

We split this skill into the rules it gives an agent

1 rule. 0 are common, 0 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 189 edited versions we read keep these.

  • 0

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Create, read, edit, and template Microsoft Word .docx files with python-docx via small CLIs.

    line 19

“Common” is measured: kept by at least 6 in 10 of the 189 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Docx Skill

Create, read, edit, and template Microsoft Word .docx files with python-docx via small CLIs. It handles text, styles, lists, tables, images, headers/footers, {{token}} templating, tracked changes (list/accept/reject), comments (list/add/delete), TOC and page-number fields, and package health checks. It does not render documents itself (PDF needs LibreOffice — see Converting to PDF in references/usage.md) or edit legacy .doc.

Global rules

  • Run every helper through scripts/; never sed or unzip-edit the XML. Raw text substitution in document.xml corrupts files easily — use the provided scripts (see references/xml-editing.md for the toolchain).
  • Verify after every produce-or-edit action. Re-read the output with docx_read.py --text/--structure, and run docx_validate.py after any revision, comment, or field surgery (checklist in references/usage.md).
  • Always normalize before find-replace on Word-edited documents. Word fragments text into runs; docx_edit.py normalize merges equal-format adjacent runs so later matches succeed.
  • Template redlining requires reading references/xml-editing.md first. The raw-XML toolchain under scripts/xml-toolchain/ is for direct OOXML access only; edit the template in place, never recreate it.

Routing

StepReferencePurpose
Commands + procedurereferences/usage.mdPrerequisites, quick-reference command table, end-to-end procedure, Converting to PDF, and the post-edit verification checklist.
Raw-XML toolchainreferences/xml-editing.mdUnpack/repack, redlining, .dotx templates, tracked changes via LibreOffice.
Tracked changes + commentsreferences/revisions-and-comments.mdRevision types, acceptance flow, comment threading, and which edge cases to hand to Word.
Edge-case behaviorsreferences/pitfalls.mdRun fragmentation, revision coverage limits, field results, validation semantics, style numbering, cell formatting, and encoding.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free