List rug collections
list_collectionsList the current Carpetstory rug collections with their story, materials, knot density, lead time and number of pieces.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
list_collectionsList the current Carpetstory rug collections with their story, materials, knot density, lead time and number of pieces.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered; the description adds value by naming the catalog contents returned. It does not mention whether the list is paginated or whether all collections are always returned, which would complete the picture.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence with the resource first and the returned fields after — no filler, nothing to trim.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description carries the return-shape burden and does so by listing the fields. Only the ordering/volume of results is unspecified, which is a minor gap for a zero-parameter listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so there is nothing for the description to disambiguate; baseline applies. No parameter-level wording is needed or missing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ('List') and resource ('Carpetstory rug collections') and enumerates the attributes returned (story, materials, knot density, lead time, piece count). It does not contrast itself with get_rug or search_rugs, but the distinct resource makes the difference inferable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is only implied: an agent can infer this is the browse-all-collections entry point versus get_rug for one rug or search_rugs for filtered lookup. No explicit when-to-use or when-not-to-use statement is given.
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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