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clidey

whodb-cli

Official

whodb_schemas

Read-onlyIdempotent

List all schemas in a database to understand its organization. Use this before exploring tables or querying data.

Instructions

List all schemas (namespaces) in a database.

Best for: Discovering what schemas exist in a database; understanding database organization before exploring tables. Not recommended for: When you already know the schema name (proceed directly to whodb_tables). Common mistakes: Calling this repeatedly - schema lists rarely change during a session.

Usage Example:

{
  "name": "whodb_schemas",
  "arguments": {
    "connection": "mydb"
  }
}

Returns: Array of schema names (e.g., ["public", "analytics", "audit"]). Typical workflow: whodb_schemas → whodb_tables(include_columns=true) → whodb_query

Optional parameter: Set "include_tables": true to also return all tables within each schema in a single call. This populates a "details" array with schema names and their tables, saving you a separate whodb_tables call per schema.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
connectionYesConnection name (optional if only one exists)
include_tablesNoSet true to also return tables within each schema in a single call

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
schemasYes
detailsNo
errorNo
request_idNo
Behavior4/5

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

Annotations already indicate read-only and idempotent behavior. Description adds useful context about schema list stability and the effect of the optional include_tables parameter, but the core behavioral traits are captured by 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 (best for, not recommended, common mistakes, example, returns, workflow). Every sentence is informative and not redundant.

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?

Given the simple nature of the tool (2 params, list result), the description fully covers usage, alternatives, and behavioral notes. Output format is described, and annotations plus schema fill remaining gaps.

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%, so baseline is 3. The description adds workflow context, example, and clarifies the optional parameter's effect, providing extra value beyond the schema.

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?

The description clearly states 'List all schemas (namespaces) in a database' with a specific verb and resource. It distinguishes from sibling tools by recommending whodb_tables when schema name is known.

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?

Provides explicit 'Best for', 'Not recommended for', and 'Common mistakes' sections. Names direct alternative (whodb_tables) and outlines a typical workflow.

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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