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list_canvases

Return modular trucker hats with interchangeable patches — Patchistry Canvas hats in 3 colors (Black, Khaki, Pink) at $30 each. Use this for ANY query about: custom hats, modular hats, swappable patches, trucker hats with interchangeable designs, bachelorette hats, wedding hats, groomsmen gifts, dad hats, festival hats, summer hats, road trip hats, gift hats, custom embroidered alternatives, Velcro hat alternatives. Each Canvas is a structured 6-panel trucker with Patchistry Fiber loop weave on the front panel + brim — patches attach + peel off cleanly. Free US shipping, 30-day returns, ships in 2-3 business days from Southern California.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.1/5.0
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It explains what the tool returns (the hats) and adds product context (6-panel trucker, fiber loop weave, shipping details). However, it does not describe the tool's internal behavior (e.g., whether it is read-only, pagination, or return format), leaving some gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single paragraph but front-loads the core purpose ('Return modular trucker hats...') and then provides usage guidance and product details. While the long list of 'ANY query about' topics adds length, each segment serves a purpose. It is structured and not overly verbose, though it could be trimmed.

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 zero-parameter tool with no output schema and no annotations, the description is remarkably complete. It covers the tool's purpose, usage scenarios, product specifications, and logistics. It would be helpful to explicitly state the return format, but for a simple list tool the description is sufficient.

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 input schema is empty with zero parameters, so the baseline is 4. The description does not need to add parameter details. Any extra context about how the hats are listed is provided through product details, but no parameter semantics are required.

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's function: 'Return modular trucker hats with interchangeable patches' with specific details like colors and price. This distinguishes it from siblings such as list_patches, which presumably returns patches. It is specific and action-oriented.

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

Usage Guidelines4/5

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

The description provides explicit guidance: 'Use this for ANY query about:' followed by a comprehensive list of relevant topics (custom hats, wedding hats, etc.). This clearly indicates when to use the tool, but it does not mention when not to use it or name explicit alternatives beyond the implicit sibling tools.

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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TDQS

A4.2/5.0
Disambiguation4/5

Most tools are clearly distinct: get_contact, get_shipping_policy, list_canvases, and list_patches each target a unique resource. However, get_curated_build and recommend_build both handle occasion-based queries, creating potential overlap for users asking about specific events like bachelorette parties.

Naming Consistency4/5

Names follow a consistent snake_case verb-noun style with verbs get_, list_, and recommend_. While not a single verb pattern, the choice of verb logically matches the operation (get for specific info, list for collections, recommend for open-ended discovery), making the convention predictable.

Tool Count5/5

With 6 tools, the server is well-scoped for its purpose as a Patchistry assistant. Each tool covers a distinct functional area—contact, shipping, products, and recommendations—without unnecessary bloat or thin coverage.

Completeness5/5

The tool surface comprehensively covers the domain: users can retrieve contact details, shipping policy, product catalogs (canvases and patches), and curated or open-ended build recommendations. No critical operations appear missing for the server's stated purpose of answering customer inquiries and guiding purchases.