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clidey

whodb-cli

Official

whodb_diff

Read-onlyIdempotent

Detect schema differences between two database connections, such as staging and production, by comparing storage units, columns, and relationships.

Instructions

Compare schema metadata between two database connections.

Best for: Spotting drift between environments; comparing staging vs production; reviewing storage-unit, column, and relationship changes. Not recommended for: Row-level data comparison. Common mistakes: Forgetting to specify both connections; comparing the same connection and schema without overrides.

Usage Example:

{
  "name": "whodb_diff",
  "arguments": {
    "from_connection": "staging",
    "to_connection": "prod",
    "from_schema": "public",
    "to_schema": "public"
  }
}

Returns: A structured schema diff with storage-unit, column, and relationship summaries plus per-object changes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
from_connectionYesSource connection name
to_connectionYesTarget connection name
from_schemaNoSource schema override
to_schemaNoTarget schema override

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNo
errorNo
request_idNo
Behavior4/5

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

Annotations already indicate readOnlyHint and idempotentHint. The description adds that it returns a structured schema diff with specific categories, and does not contradict annotations. No further behavioral details needed.

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-organized with clear sections (purpose, best for, not recommended, common mistakes, usage example, returns). 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?

Given 4 parameters and existing output schema, the description fully covers usage context, including pitfalls and expected return format. No gaps identified.

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 the description adds value by showing a usage example and clarifying parameter roles in common mistakes, beyond the schema descriptions.

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 the tool compares schema metadata between two connections, with specific verb and resource. It distinguishes from siblings by specifying it's for schema-level comparison, not row-level data.

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 scenarios (drift detection, staging vs prod), not-recommended (row-level data), and common mistakes (forgetting both connections, comparing same connection without overrides).

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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