Use sql_db_list_tables tool to see all available tables in the database.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionschema-explorationExecute the skills CLI command in your project's root directory to begin installation:
Fetches schema-exploration from langchain-ai/deepagents and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate schema-exploration. Access via /schema-exploration in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Use sql_db_list_tables tool to see all available tables in the database.
This returns the complete list of tables you can query.
Use sql_db_schema tool with table names to examine:
Identify how tables connect:
Provide clear information about:
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
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
Step 1: Identify tables needed
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.
For "list tables" questions:
For "describe table" questions:
For "how do I query X" questions:
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
jezweb/claude-skills
schema-exploration reduced setup friction for our internal harness; good balance of opinion and flexibility.
schema-exploration is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: schema-exploration is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend schema-exploration for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: schema-exploration is the kind of skill you can hand to a new teammate without a long onboarding doc.
schema-exploration is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in schema-exploration — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Useful defaults in schema-exploration — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
schema-exploration has been reliable in day-to-day use. Documentation quality is above average for community skills.
schema-exploration has been reliable in day-to-day use. Documentation quality is above average for community skills.
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