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clidey

whodb-cli

Official

whodb_suggestions

Read-onlyIdempotent

Generate starter SQL queries for a schema or database to help users orient themselves in unfamiliar storage units with onboarding hints.

Instructions

Load backend-generated starter queries for a schema or database.

Best for: Quickly orienting yourself in an unfamiliar database; suggesting first queries for exploration. Not recommended for: Exhaustive SQL tutoring. Common mistakes: Treating the suggestions as guaranteed-valid business logic rather than onboarding hints.

Usage Example:

{
  "name": "whodb_suggestions",
  "arguments": {
    "connection": "mydb",
    "schema": "public"
  }
}

Returns: A short list of backend-generated query suggestions derived from the actual storage units in the resolved schema.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
connectionYesConnection name (optional if only one exists)
schemaNoSchema or database name override

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
suggestionsYes
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 context about suggestions being derived from actual storage units, returning a short list, and warns against treating them as guaranteed-valid business logic.

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?

The description is concise with clear structure: bullet points, headings, and a usage example. Every sentence adds value without 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?

Given full parameter coverage, annotations, and known output schema, the description covers purpose, usage, return type, and pitfalls, making it complete for an AI agent.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already explains the two parameters. The description provides a usage example but no additional semantic detail 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 it loads backend-generated starter queries, includes a specific verb ('Load') and resource, and distinguishes from siblings via 'Best for' and 'Not recommended for' sections.

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?

Explicit 'Best for' and 'Not recommended for' sections provide clear guidance on when to use (orienting in unfamiliar database) and when not to use (exhaustive SQL tutoring), plus a 'Common mistakes' caution.

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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