Agent skill · Data & Analytics

lab-report-writer

Use for writing, editing, polishing, or structuring lab reports and course experiment reports across disciplines. Handles cases with a provided template, raw data, images, notes, or only a brief requirement, and can produce DOCX or Markdown deliverables.

mingchen666157★ · +54/wk · 1 repos on radarProfile →
claude-coderead-only
Install
npx skills add mingchen666/Reviva --skill lab-report-writer --agent claude-code

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

Facts
Files in the skill folder: 2
SKILL.md size: 2 KB
Bundled scripts: none
Allowed tools: document_readoffice_writefile_readfile_writekb_searchweb_search_bing
Path: electron/builtin-assets/skills/lab-report-writer/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 181 · +24 this week
Language: HTML
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

# 实验报告写作 ## 目标 帮助用户完成可提交的实验报告,而不是只生成泛泛的说明文字。默认面向高校课程、专业课实验、课程设计小实验和训练性实验,覆盖物理、化学、生物、材料、电子电路、自动化、计算机、机械、心理学、环境、医学基础等常见方向。 ## 输入类型 用户可能只提供其中一部分: - 实验名称、课程名、专业方向、教师要求。 - 实验指导书、讲义、评分标准、知识库资料。 - Word 模板、历史报告、待补全文档。 - 原始数据、表格、截图、实验照片、仪器输出文件。 - 只说一句“帮我写某某实验报告”。 不要因为缺少全部材料就停止。能合理生成框架时先生成;不能确定的数据、图片、个人操作记录、教师指定格式必须标为“待补充”,不要编造。 ## 总流程 1. 识别实验类型、交付格式、是否有模板、是否有原始数据。 2. 有模板时,先用 `document_read` 读取模板结构,再用 `offi

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About this skill
What does the lab-report-writer skill do?

Use for writing, editing, polishing, or structuring lab reports and course experiment reports across disciplines. Handles cases with a provided template, raw data, images, notes, or only a brief requirement, and can produce DOCX or Markdown deliverables.

How do I install it?

Run `npx skills add mingchen666/Reviva --skill lab-report-writer --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 mingchen666/Reviva, a repository with 181 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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