Agent skill · Documentation

docx-comment-reply

Reply to comments (批注) in Word .docx/.doc files: extract comment context, draft replies, write threaded replies back, and validate OOXML.

foryourhealth111-pixelgithub.com/foryourhealth111-pixelGitHub ↗
claude-codecodexships scriptsApache-2.0
Install
npx skills add foryourhealth111-pixel/Vibe-Skills --skill docx-comment-reply --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 5
SKILL.md size: 2 KB
Bundled scripts: yes
Path: bundled/skills/docx-comment-reply/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,593
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Word 批注回复(.docx/.doc) 这个 skill 解决的问题:把 Word 文档里的批注(comments)按“原文锚点上下文”整理出来,生成待回复清单,然后把回复以 **threaded replies** 的方式写回到新的 `.docx` 文件里(不改原文件)。 适用场景:专利/论文/合同/内部评审等需要“逐条回复批注”的文档。 ## 输出物(约定) 在当前工作目录的 `outputs/` 下生成: - `*_批注定位与上下文_*.md`:人可读的批注+锚点上下文报告 - `*_comment_context_*.json`:机器可读上下文(用于并行写回复/自动化) - `*_replies_todo_*.json`:待回复模板(键=comment_id,值=空字符串) - `*_批注已回复_*.docx`:写回批注回复后的最终交付文件 ## 工作流(推荐) ### 1

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About this skill
What does the docx-comment-reply skill do?

Reply to comments (批注) in Word .docx/.doc files: extract comment context, draft replies, write threaded replies back, and validate OOXML.

How do I install it?

Run `npx skills add foryourhealth111-pixel/Vibe-Skills --skill docx-comment-reply --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From foryourhealth111-pixel/Vibe-Skills, a repository with 2,593 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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