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EldanRingEldanRing/qubicl/skills/core/docx/SKILL.md

docx

Skill13 starsChanged 3 months agoApache-2.0View on GitHub

Create, read, edit, template, validate, and review Word DOCX documents using Qubicl's pinned local document tools. Use for professional Word documents, tracked revisions, comments, structured edits, and DOCX templates.

194 other projects use a version of this.

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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

3 rules. 0 are common, 0 are distinctive, and 3 are 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.

  • 3

    Very specific

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

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

    Keep inputs and outputs under /home/qubicl.

    line 8
  2. Very specific:

    Read references/revisions-and-comments.md only for tracked-change or comment work.

    line 19
  3. Very specific:

    Use the common rendering receipt for PDF, DOCX, XLSX and PPTX: /opt/qubicl/skills-venv/bin/python /opt/qubicl/artifact-render.py FILE …

    line 23

“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 workflows

Keep inputs and outputs under /home/qubicl. Obtain this skill's resourceRoot from skill_view and run bundled helpers with /opt/qubicl/skills-venv/bin/python. Qubicl computer and workstation images contain the pinned libraries; never install dependencies as part of the workflow.

Useful helpers beneath <resourceRoot>/scripts/:

  • docx_read.py FILE --text|--structure|--styles|--revisions [--mode final|original|markup]
  • docx_create.py SPEC.json OUTPUT.docx
  • docx_edit.py for text, paragraph, style, and table-cell edits
  • docx_template.py TEMPLATE.docx VALUES.json OUTPUT.docx
  • docx_comments.py and docx_revisions.py
  • docx_validate.py FILE

Read references/revisions-and-comments.md only for tracked-change or comment work.

Inspect before editing, write to a new output unless in-place work was requested, and validate after every mutation. On workstation computers, use LibreOffice for a final PDF render when visual layout matters; on computer computers, report that structured DOCX operations work but office rendering may be unavailable. Preserve unknown OOXML parts whenever a helper supports doing so.

Use the common rendering receipt for PDF, DOCX, XLSX and PPTX: /opt/qubicl/skills-venv/bin/python /opt/qubicl/artifact-render.py FILE --outdir DIR. Each invocation captures its source, uses an isolated Office profile, and writes a unique run directory with PDF, exact numbered PNGs and manifest.json. Read sourceSha256, pages, warnings and validation, then inspect the generated pages. Old previews are never returned as this run's outputs. visuallyInspected: false is intentional: the tool renders; the agent performs visual review. Office rendering needs workstation.

Text replacements use original matches once and preserve drawings and run properties. Edits across unsupported tabs/breaks/field structures fail explicitly. Comment anchors use consistent text offsets across tabs, line breaks, position tabs and nonbreaking hyphens; splitting preserves inline objects, and comment reads retain tabs and line breaks in both anchor text and comment bodies.

Template filling substitutes each original {{token}} once, including whitespace variants and tokens spanning formatted runs. Values are literal: a value containing {{another_token}} is retained as text and is never expanded recursively. Results are deterministic; replacement text inherits the first matched run's formatting. filled counts original substitutions and unfilled_tokens lists original placeholders lacking supplied values. --strict fails only for those unresolved original placeholders, not token-like text deliberately supplied as a value. An unresolved strict template returns output_written: false and leaves an existing destination untouched.

Read tracked documents with --mode final (default, accept revisions in memory), --mode original (reject them in memory), or --mode markup (both views and anchored revision records). Reading preserves the source file. These modes resolve inserted/deleted/moved content, paragraph marks, revised rows/cells and property snapshots across body content, nested tables, all header/footer variants, notes, comments and text boxes. Text JSON includes ordered blocks, headerStories/footerStories, footnotes, endnotes, comments and textboxes, alongside the compatible body/tables/headers/footers fields. Include the related stories when reviewing the whole document. Revision records identify the original package part, XML path, author/date, context and previous/current properties. Use docx_revisions.py only when an accepted/rejected output file is wanted; --part can scope a reused revision ID to one story. Text extraction reports stored field results; rendering remains the way to inspect pagination and visual appearance.

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