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farm_storefront

List every data product on sale: routes, prices, input/output shapes, the fresh-or-free guarantee, and how to pay. Free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral disclosure burden. It communicates that this is a read-only listing operation ('List'), discloses the fresh-or-free guarantee, and mentions payment mechanics, which is useful beyond a bare catalog description. It could add explicit statements about auth requirements or response shape, but the core behavior is clear for a zero-parameter listing tool.

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?

Two short sentences, tightly packed with useful information and no filler. The main resource is stated first, followed by a colon-delimited list of included details, and the final standalone 'Free' adds cost context without disrupting flow.

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?

For a simple zero-parameter catalog tool with no output schema, the description covers the key things an agent needs: what the listing includes, pricing, guarantee, and payment path. It is slightly thin on whether access or authentication is required to use the storefront itself, but the core selection context is complete.

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?

The tool has zero parameters, so the baseline is 4. The description adds no parameter details because there are none, but it compensates by describing exactly what kind of data the returned product list will contain, which is the relevant semantic information for an agent.

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 states a specific action ('List every data product on sale') and a clear resource (the storefront catalog). It enumerates the catalog's contents (routes, prices, I/O shapes, guarantees, payment), which distinguishes it from sibling farm tools that deliver specific data products rather than catalog them.

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 implied use is clear: call this when you need to browse available data products and their terms. However, there is no explicit guidance about when not to use it, no named alternatives, and no exclusions. The description relies on the agent inferring that farm_storefront is the catalog while siblings are the actual data endpoints.

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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