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Mav977

AutoMCP-SQL

by Mav977

create_orders

Insert a new order record into the orders table by supplying a JSON string of column values. Enables direct data entry through a generated CRUD interface, avoiding raw SQL.

Instructions

Insert a new row into orders. data = JSON string like '{"col":"val"}'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

There are no annotations, so the description must carry the behavioral disclosure burden. It states the action ('Insert') but doesn't disclose side effects, validation behavior, or response handling. It also doesn't clarify whether the operation is idempotent or whether it returns the created record.

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 two sentences, with the main purpose front-loaded and a compact example. No redundant information, every word earns its place.

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

Completeness3/5

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

Given the tool's simplicity (one parameter) and the existence of an output schema, the description covers the essential operation. However, it lacks information about required fields or constraints, and the generic example may not fully prepare an agent to construct valid data without additional context.

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?

The input schema only defines 'data' as a string with no description. The description compensates by specifying that data is a JSON string and provides an example format ('{"col":"val"}'), which adds meaning beyond the schema. However, it doesn't enumerate valid column names for the orders table, leaving some ambiguity.

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 'Insert a new row into orders.' This provides a specific verb and resource, and the resource name distinguishes it from sibling create_* tools like create_users or create_products.

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

Usage Guidelines3/5

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

The description implies that this tool is for adding new order records, matching the name create_orders. However, it doesn't explicitly say when to use it versus alternatives, nor does it mention any prerequisites or exclusions, so usage context is only implied.

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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