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Mav977

AutoMCP-SQL

by Mav977

get_orders

Retrieve order records from a SQLite database. Use an optional JSON filter string to return specific rows by column values, or leave empty for all orders.

Instructions

Get rows from orders. filters = JSON string like '{"col":"val"}' or empty string for all rows.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filtersNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the JSON filter format and the special case for empty string, which is useful. However, it does not mention output structure (though an output schema exists), error handling, or any other behavioral traits, leaving the transparency minimal but adequate for a simple read operation.

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 a single sentence that packs in the action, the resource, and the parameter format. It is front-loaded and free of unnecessary words, earning a perfect score for conciseness.

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

Completeness4/5

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

The tool is simple with one optional parameter and an output schema, so the description need not explain return values. The parameter semantics are fully covered, and the purpose is clear. However, it lacks any mention of use cases relative to siblings or potential prerequisites, preventing a perfect score.

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

Parameters5/5

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

The schema only defines filters as a string with a default value and has 0% description coverage. The tool description fully compensates by specifying the exact JSON format ('{"col":"val"}') and the meaning of an empty string (all rows), adding critical meaning 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 the tool fetches rows from the orders table, using the specific verb 'Get' and the resource 'rows from orders'. This distinguishes it from sibling tools like create_orders, update_orders, and delete_orders, as well as other get_* tools.

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 provides context for the filters parameter (empty string returns all rows) but does not explicitly mention when to use this tool versus alternatives like create_orders or get_users. Usage is implied rather than explicitly differentiated, making it minimally viable but not richly guided.

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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