schema-exploration
Lists tables, describes columns and data types, identifies foreign key relationships, and maps entity relationships in a database.
Skill by langchain-aiOfficial
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/langchain-ai-schema-exploration
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About
Use cases: backend, data, agent-building, database-access
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/schema-exploration
What's inside
- Skill name
schema-exploration- Description
- 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.
- License
- MIT
- Instructions
- 129 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# 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
From langchain-ai/deepagents, MIT.
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Signals
- Stars
- 30,550
- Forks
- 4,302
- Open issues
- 163
- Last commit (this folder)
- Mar 17, 2026 (7 months ago)
- Last release
- Oct 23, 2026 (3 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/langchain-ai/deepagents
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
schema-exploration skill. Agent Mart. https://agentmart.dev/skills/langchain-ai-schema-exploration (last updated 2026-10-24)