Schema Exploration logo

Schema Exploration

OrganizationPopular
langchain-ai
schema-exploration

Lists tables, describes columns and data types, identifies foreign key relationships, and maps entity relationships in a database. Use when the user asks about database schema, table structure, column types, what tables exist, ERD, foreign keys, or how entities relate.

Overview

Publisherlangchain-ai
Repositorydeepagents
Skill nameschema-exploration
Stars
29.9K
Forks
4.2K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by langchain-ai on GitHub. Read the source before you install it.

Installation

Install the Schema Exploration AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/langchain-ai/deepagents/tree/main/examples/text-to-sql-agent/skills/schema-exploration
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/langchain-ai/deepagents.git /tmp/deepagents
mkdir -p .claude/skills
cp -r /tmp/deepagents/examples/text-to-sql-agent/skills/schema-exploration .claude/skills/schema-exploration
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Schema Exploration in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Schema Exploration on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Schema Exploration is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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)

Frequently asked questions

What does the Schema Exploration AI skill do?

Lists tables, describes columns and data types, identifies foreign key relationships, and maps entity relationships in a database. Use when the user asks about database schema, table structure, column types, what tables exist, ERD, foreign keys, or how entities relate.

Why use Schema Exploration on TypingMind?

Because you install it once and use it with any model. Schema Exploration is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Schema Exploration in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/langchain-ai/deepagents/tree/main/examples/text-to-sql-agent/skills/schema-exploration. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Schema Exploration?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Schema Exploration?

As many as you like. As long as a model supports skills, you can use Schema Exploration with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Schema Exploration AI skill free?

Yes. It is published on GitHub by langchain-ai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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