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convert-sc-design-hblab转换 sc 设计 hblab

Agent Skill

用于辅助界面设计、视觉规范、排版、配色、布局和交互体验优化。它适合让 Agent 根据产品场景整理页面结构、生成 UI 方案、检查视觉一致性或改进组件层级。使用时需要结合现有品牌、设计系统和用户任务,不应只堆装饰元素;涉及真实页面改动时,应通过截图或浏览器预览检查文本溢出、对齐和响应式表现。

总安装

374

周安装

15

GitHub Stars

1

下载量

121
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:convert-sc-design-hblab(转换 sc 设计 hblab)
来源仓库:https://github.com/datht-hblab-company/convert-sc-design-hblab
仓库路径:skills/convert-sc-design-hblab
安装命令:
npx skills add https://github.com/datht-hblab-company/convert-sc-design-hblab --skill convert-sc-design-hblab
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/datht-hblab-company/convert-sc-design-hblab --skill convert-sc-design-hblab

简介

convert-sc-design-hblab 读取 Google Sheets 表格并生成结构化 Markdown 文档。

  • 适用于设计规范提取、团队协作知识沉淀或 UI 组件说明编写。
  • 需配置 OAuth 凭据并通过 ~/.config/google-sheets/oauth-token.json 认证。
  • 输出文件写入当前工作空间的 ./docs 目录,不污染技能安装路径。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

convert-sc-design-hblab

Read a Google Sheet by SPREADSHEET_ID and turn the result into usable markdown.

Requirements

  • OAuth credentials at ~/.config/google-sheets/oauth-token.json with:

- client_id - client_secret - refresh_token

  • Google Sheets API enabled for that OAuth app

Output Policy

  • Use the installed script from the skill directory, but write any authored markdown into ./docs of the current workspace.
  • If ./docs does not exist, create it before writing files.
  • Do not save generated documents into the installed skill directory.

Usage

Step 1: Resolve the installed script path

SKILL_DIR is the directory containing this skill — the directory from which this SKILL.md was loaded. It contains scripts/read_sheet.py. Each agent resolves this from its own skill registry; no hardcoded path is needed.

Step 1.5: Extract the spreadsheet ID

If the user gave a URL like: https://docs.google.com/spreadsheets/d/1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms/edit#gid=0

The spreadsheet ID is the segment between /d/ and the next /: 1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms

# Extract from URL (bash)
SPREADSHEET_ID=$(echo "$URL" | sed 's|.*/d/\([^/]*\).*|\1|')

If the user gave a raw alphanumeric ID with no slashes, use it directly.

Step 2: Fetch sheet data

python3 "$SKILL_DIR/scripts/read_sheet.py" --spreadsheet-id "$SPREADSHEET_ID" --sheet-name <SHEET_NAME>

If the caller already has a Google Sheets tab id from the URL, they can target it directly:

python3 "$SKILL_DIR/scripts/read_sheet.py" --spreadsheet-id "$SPREADSHEET_ID" --gid <GID>

Step 2.5: Discover the sheet name

If the user did not specify a sheet name, omit --sheet-name — the script reads the first sheet by default. If the user provides both --sheet-name and --gid, --gid overrides --sheet-name.

To inspect headers and data shape before committing to a format, always run json first:

python3 "$SKILL_DIR/scripts/read_sheet.py" \
  --spreadsheet-id "$SPREADSHEET_ID" \
  --format json

Ask the user whether they want to read additional sheets if the spreadsheet has multiple tabs. Always preserve the full sheet content unless the user explicitly asks for summarization.

Step 3: Classify data shape and format accordingly

After inspecting the JSON output, classify the data:

ShapeSignsRecommended approach
TabularRow 0 = headers, rows 1+ = records--format table, add heading + 1-sentence description
Key-value / configTwo columns (key, value)Don't use a table — render as ## Key / value prose
Pivot / cross-tabFirst col = label, remaining = categories--format table, note pivot structure above table
Free text / notesIrregular rows, no clear header--format text, render each row as a paragraph or bullet

Step 4: Write the markdown document

Structure:

# <Spreadsheet Title or User-Provided Name>

> Source: Google Sheet — <Sheet Name> (ID: <SPREADSHEET_ID>)

## <Section heading derived from content>

<Formatted content>
  • Derive the title from context or ask the user.
  • Always include the source line.
  • Save to ./docs/<sheet-name-kebab-case>.md. Create ./docs first: mkdir -p./docs

Parameters

ParameterRequiredDescription
--spreadsheet-idYesThe Google Spreadsheet ID
--sheet-nameNoSheet name to read. Defaults to the first sheet.
--gidNoGoogle Sheets tab id / sheetId. Overrides --sheet-name when both are set.
--credentialsNoOAuth credentials path. Defaults to ~/.config/google-sheets/oauth-token.json.
--outputNoOutput file path. Defaults to stdout.
--formatNoOutput format: json (default), table, or text.
--rawNoKeep empty columns instead of cleaning them.

Example

# Fetch as JSON
python3 "$SKILL_DIR/scripts/read_sheet.py" \
  --spreadsheet-id "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms" \
  --gid "0"

# Fetch as markdown table
python3 "$SKILL_DIR/scripts/read_sheet.py" \
  --spreadsheet-id "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms" \
  --sheet-name "Sheet1" \
  --format table

# Save raw output directly into the current workspace docs folder
mkdir -p ./docs
python3 "$SKILL_DIR/scripts/read_sheet.py" \
  --spreadsheet-id "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms" \
  --gid "0" \
  --format table \
  --output ./docs/sheet1.md

OAuth Credentials Format

{
  "type": "oauth",
  "client_id": "your-client-id.apps.googleusercontent.com",
  "client_secret": "your-client-secret",
  "refresh_token": "your-refresh-token"
}

First-Run Setup

If credentials don't exist at ~/.config/google-sheets/oauth-token.json:

  1. Create a Google Cloud project, enable the Google Sheets API
  2. Create an OAuth 2.0 Desktop app credential → download JSON
  3. Get a refresh token via https://developers.google.com/oauthplayground/

- Use scope: https://www.googleapis.com/auth/spreadsheets.readonly

  1. Create the credentials file: mkdir -p ~/.config/google-sheets # Write the JSON with client_id, client_secret, refresh_token

For detailed steps, see docs/troubleshooting.md in the source repo.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

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能力 2

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能力 3

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能力 4

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安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.78%
按下载量换算43

Claude

31.25%
按下载量换算38

Cursor

20.12%
按下载量换算24

Gemini CLI

9.44%
按下载量换算11

安全审计

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通过

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通过

Snyk

可疑

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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