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schema-exploration图式探索

Agent Skill

schema-exploration 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。

总安装

9,987

周安装

404

GitHub Stars

21,964

下载量

3,135
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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

3

许可证

MIT

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:schema-exploration(图式探索)
来源仓库:https://github.com/langchain-ai/deepagents
仓库路径:skills/schema-exploration
安装命令:
npx skills add https://github.com/langchain-ai/deepagents --skill schema-exploration
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/langchain-ai/deepagents --skill schema-exploration

简介

用于查找、检索和筛选相关信息,支持根据关键词定位候选结果。

  • 适合在任务场景中快速获取线索或缩小搜索范围。
  • 可结合原始 README 核验实际用法,确保与预期场景匹配。
  • 安装前建议确认维护状态及是否依赖外部网络调用。
  • schema-exploration 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Schema Exploration Skill

Workflow

1. List All Tables

Use sql_db_list_tables tool to see all available tables in the database.

This returns the complete list of tables you can query.

2. Get Schema for Specific Tables

Use sql_db_schema tool with table names to examine:

  • Column names - What fields are available
  • Data types - INTEGER, TEXT, DATETIME, etc.
  • Sample data - 3 example rows to understand content
  • Primary keys - Unique identifiers for rows
  • Foreign keys - Relationships to other tables

3. Map Relationships

Identify how tables connect:

  • Look for columns ending in "Id" (e.g., CustomerId, ArtistId)
  • Foreign keys link to primary keys in other tables
  • Document parent-child relationships

4. Answer the Question

Provide clear information about:

  • Available tables and their purpose
  • Column names and what they contain
  • How tables relate to each other
  • Sample data to illustrate content

Example: "What tables are available?"

Step 1: Use sql_db_list_tables

Response:

The Chinook database has 11 tables:
1. Artist - Music artists
2. Album - Music albums
3. Track - Individual songs
4. Genre - Music genres
5. MediaType - File formats (MP3, AAC, etc.)
6. Playlist - User-created playlists
7. PlaylistTrack - Tracks in playlists
8. Customer - Store customers
9. Employee - Store employees
10. Invoice - Customer purchases
11. InvoiceLine - Individual items in invoices

Example: "What columns does the Customer table have?"

Step 1: Use sql_db_schema with table name "Customer"

Response:

The Customer table has these columns:

- CustomerId (INTEGER) - Primary key, unique customer ID
- FirstName (NVARCHAR) - Customer's first name
- LastName (NVARCHAR) - Customer's last name
- Company (NVARCHAR) - Company name (optional)
- Address, City, State, Country, PostalCode - Location fields
- Phone (NVARCHAR) - Phone number
- Fax (NVARCHAR) - Fax number
- Email (NVARCHAR) - Email address
- SupportRepId (INTEGER) - Foreign key to Employee table

Sample data shows customers like:
- Luís Gonçalves from Brazil
- Leonie Köhler from Germany
- François Tremblay from Canada

Example: "How do I find revenue by artist?"

Step 1: Identify tables needed

  • Artist (has artist names)
  • Album (links artists to tracks)
  • Track (links albums to sales)
  • InvoiceLine (has sales data)
  • Invoice (has revenue totals)

Step 2: Map relationships

Artist (ArtistId)
  ↓ 1:many
Album (ArtistId, AlbumId)
  ↓ 1:many
Track (AlbumId, TrackId)
  ↓ 1:many
InvoiceLine (TrackId, UnitPrice, Quantity)

Response:

To find revenue by artist, you'll need to:
1. Start with the Artist table
2. JOIN to Album on ArtistId
3. JOIN to Track on AlbumId
4. JOIN to InvoiceLine on TrackId
5. SUM the revenue (UnitPrice * Quantity)
6. GROUP BY artist name

This requires the query-writing skill to execute.

Quality Guidelines

For "list tables" questions:

  • Show all table names
  • Add brief descriptions of what each contains
  • Group related tables (e.g., music catalog, transactions, people)

For "describe table" questions:

  • List all columns with data types
  • Explain what each column contains
  • Show sample data for context
  • Note primary and foreign keys
  • Explain relationships to other tables

For "how do I query X" questions:

  • Identify required tables
  • Map the JOIN path
  • Explain the relationship chain
  • Suggest next steps (use query-writing skill)

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

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

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

Claude Code

26.38%
按下载量换算827

OpenCode

25.18%
按下载量换算789

Cursor

19.53%
按下载量换算612

Codex

12.83%
按下载量换算402

Antigravity

8.37%
按下载量换算262

Gemini CLI

3.58%
按下载量换算112

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。

来源信息

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