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Agent Skill · 研究检索

dot(点)

dot 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

dot 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 35,926。

总安装 2,002周安装 81GitHub Stars 公开资料未说明下载 629核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:dot(点)
来源仓库:https://github.com/snowboard-software/getdot
仓库路径:skills/dot
安装命令:
npx skills add https://github.com/snowboard-software/getdot --skill dot
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/snowboard-software/getdot --skill dot

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

dot 查询公司数据库,由 AI 分析师生成 SQL 与可视化结果。适用于销售、客户与财务数据洞察,支持自然语言转查询。自动解释结果并提供下一步建议,降低数据分析门槛。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。

需配置数据库连接与权限,防止越权访问敏感表结构。dot 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/dot

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/snowboard-software/getdot --skill dot;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

dot 怎么安装?

在终端执行 npx skills add https://github.com/snowboard-software/getdot --skill dot。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

dot 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

dot 需要什么权限?

权限级别是接触敏感数据。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。

dot 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

dot 用的人多吗?

公开数据是累计安装 2,002 次,近一周安装 81 次,下载 629 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

dot 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
dot

点 · 本页

2,002—接触敏感数据未明确未通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

dot — AI Data Analyst CLI

dot lets you query your company's databases through Dot, an AI data analyst. Dot writes SQL, runs queries, generates charts, and explains results.

Setup

If dot is not installed or not found in PATH:

  • macOS/Linux: curl -fsSL https://app.getdot.ai/install.sh | sh
  • Windows: irm https://app.getdot.ai/install.ps1 | iex

After installing, authenticate with dot login (opens browser).

When to use

Use dot when the user asks about:

  • Data questions: "What were sales last month?", "Show me top customers"
  • Metrics and KPIs: "What's our churn rate?", "Revenue by region"
  • SQL queries: "Write a query to find...", "Check the database for..."
  • Reports: "Generate a summary of...", "Break down..."
  • Any time they say "ask dot", "check the numbers", or "query the data"

Decision: catalog vs ask

  • If the user asks WHAT data is available, run dot catalog
  • If the question is vague (no specific metric, table, or time period), run dot catalog first to understand what's available, then ask a targeted question
  • If the user asks a specific data question, go straight to dot "..."

How to use

Discover available data first

Before asking questions, run dot catalog to see what data is available:

dot catalog

This returns instantly (no LLM call) and shows:

  • Available capabilities (SQL, visualizations, scheduled reports, text analysis)
  • Custom skills configured for the org
  • Data source connections with table counts
  • Top 50 tables sorted by usage, with descriptions and column/row counts
  • External assets (Looker dashboards, etc.)

Ask questions

Run dot via Bash with the question in quotes. Set a generous timeout — Dot runs a full AI analysis pipeline (SQL generation, execution, visualization) which takes 15-60 seconds, sometimes up to 2 minutes for complex queries:

dot "What were total sales last month?"

Follow-up questions

Every response includes a chat ID. Use --chat to continue the conversation:

dot "Now break down by region" --chat cli-m1abc2d-x4y5z6

When to bypass cache

Responses are cached permanently. Use --no-cache when:

  • The question involves "today", "right now", "latest", or "current"
  • The user says "refresh", "update", or "re-run"
  • The user seems unsatisfied with a previous answer
dot "What are today's sales numbers?" --no-cache

After receiving a response

  1. Parse the output text and present the explanation to the user
  2. If a chart PNG path is shown ("Chart saved to: /tmp/dot/...png"), READ the PNG file — you have multimodal capabilities and can describe what the chart shows
  3. If a CSV path is shown and the user needs detailed analysis, read and analyze the CSV data
  4. Present suggested follow-ups if they seem relevant to the user's goal
  5. If the user wants to continue, use --chat with the chat ID from the output

Output format

The output includes:

  • Text explanation — natural language answer to the question
  • SQL query — the exact SQL that was executed
  • Data preview — first rows as CSV-like text with column stats
  • Chart — saved as PNG to /tmp/dot/<chat-id>/ (read it — you're multimodal)
  • CSV data — saved locally for further analysis
  • Dot URL — link to the full interactive analysis in the browser
  • Suggested follow-ups — use these proactively if relevant

Multi-step analysis

You can orchestrate multi-step data analysis:

  1. Run dot catalog to understand available data
  2. Ask an initial question with dot "..."
  3. Read the CSV output for deeper analysis or custom calculations
  4. Ask follow-up questions using --chat to refine results
  5. Compare results across multiple queries

Caching

  • dot "question" — cached forever until --clear-cache
  • Follow-ups with --chat are never cached (always fresh)
  • dot catalog is never cached (already fast, no LLM)

Use --no-cache to force a fresh request, or --clear-cache to wipe all cached data.

Tips for good questions

  • Start with dot catalog to understand what tables and data are available
  • Be specific: include metric names, time periods, filters
  • One question at a time works best
  • Use follow-ups (--chat) to refine rather than asking compound questions
  • If you need a chart, say "show me a chart of..." or "visualize..."

Error: command not found

If dot is not found, tell the user to install it:

curl -fsSL https://app.getdot.ai/install.sh | sh
dot login

Error: Not authenticated

If you get "Not authenticated", the user needs to log in:

dot login

If dot login doesn't work (e.g., no browser available, SSO issues), the user can create an API token manually:

  1. Open the Dot dashboard in a browser (e.g., https://app.getdot.ai or your company's Dot URL)
  2. Go to Settings > Users > API Tokens
  3. Create a new token scoped to their user
  4. Use it with: dot login --token <TOKEN> --server <SERVER_URL>

Error: Authentication failed

If you get "Authentication failed", the token may have expired. The user needs to re-login:

dot login

Error: Connection failed

If dot can't reach the server, tell the user to check their internet connection. If using a custom server, verify the URL with dot status.

Debugging

Run dot status to check who is logged in, which server is configured, and whether the token is expired.

Examples

# See what data is available
dot catalog

# Simple question
dot "What were total sales last month?"

# With follow-up
dot "Compare to the same period last year" --chat cli-m1abc2d-x4y5z6

# Chart request
dot "Show me a chart of monthly revenue trend for the past 12 months"

# Specific filters
dot "Top 10 customers by order count in Q4 2025, US only"

# Force fresh answer (bypass cache)
dot "What were total sales last month?" --no-cache

平台分布

Codex

37.06%
按下载量换算233

Claude

25.74%
按下载量换算162

Cursor

18.34%
按下载量换算115

Gemini CLI

9.28%
按下载量换算58

安全审计

Gen Agent Trust Hub

未通过

Socket

通过

Snyk

未通过

权限和风险

接触敏感数据

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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