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clidey

whodb-cli

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whodb_columns

Read-onlyIdempotent

Retrieve column names, data types, primary keys, and foreign key relationships for a specified database table to understand table structure before writing queries.

Instructions

Describe the columns in a database table.

Best for: Understanding table structure before writing queries; discovering primary keys and foreign key relationships. Not recommended for: When you need actual data (use whodb_query with SELECT). Common mistakes: Forgetting to specify the table name; not using this before writing INSERT/UPDATE queries.

Usage Example:

{
  "name": "whodb_columns",
  "arguments": {
    "connection": "mydb",
    "table": "users",
    "schema": "public"
  }
}

Returns: Array of column objects with:

  • name: Column name

  • type: Data type (varchar, integer, timestamp, etc.)

  • is_primary: Whether this is a primary key

  • is_foreign_key: Whether this references another table

  • referenced_table/referenced_column: Foreign key target (if applicable)

Pro tip: Always call this before writing INSERT queries to ensure correct column names and types.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
connectionYesConnection name (optional if only one exists)
schemaNoSchema name (uses default if omitted)
tableYesTable name to describe

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
columnsYes
tableYes
schemaYes
errorNo
request_idNo
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint and idempotentHint. Description adds return structure details (array of column objects with fields like name, type, is_primary) and best practices beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with clear sections, front-loaded purpose, every sentence adds value, no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Output schema is present but description explains it fully. Covers purpose, parameters, return format, and use cases thoroughly for a read-only metadata tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but description adds value through usage example, pro tip about connection optionality, schema default, and common mistake about forgetting table name.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states 'Describe the columns in a database table' with specific verb and resource. Distinct from siblings: not for actual data (whodb_query) nor listing tables (whodb_tables).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly provides best-for, not-recommended-for, and common mistakes sections. Gives clear context for when to use and when alternatives are better.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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