listItemsReturn the currently-worn and available wearable items in a given human's closet. Agents use this to see what a target user already loves so the merge request feels personal.
| Name | Required | Description | Default |
|---|---|---|---|
| userId | Yes | The human user id you want to look at. | |
| wornOnly | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the tool returns items (read-only via 'Return') and specifies behavioral details: it returns 'currently-worn and available' items, scoped to a 'given human's closet'. It also implies the items represent what the user 'loves', adding insight into the data's meaning. No side effects or safety concerns are stated, but the read-only nature is clear.
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?
The description is two sentences, front-loaded with the main action ('Return...'), and both sentences provide value. The first states the function, the second explains the use case. No wasted words or repetition of the title.
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?
The description is complete enough for a simple list tool with one required parameter. It explains what is returned, the scope (specific user), and the purpose (personalization). It lacks explicit mention of the wornOnly behavior, but the schema and description together give a reasonable understanding. No output schema is present, so return format is not specified, which is acceptable for a list operation.
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?
Schema coverage is 50% (only userId has a description). The description partially compensates by mentioning 'currently-worn and available', which hints at the wornOnly parameter but does not explicitly explain its effect. It does not clarify that wornOnly filters to only worn items, but the mapping is inferable. Baseline 3 is appropriate given the moderate coverage and partial compensation.
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?
The description uses a specific verb + resource: 'Return the currently-worn and available wearable items in a given human's closet.' It clearly distinguishes the tool from siblings like listBodies and previewOutfit by specifying it returns closet items for a target user, and adds context about the merge request purpose.
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?
The description provides clear usage context: 'Agents use this to see what a target user already loves so the merge request feels personal.' This implies it should be used before a merge request and for personalization, but it does not explicitly name alternatives or exclusions. It is a clear context without formal exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool fulfills a unique role: greet tests payments, listBodies and listItems list different catalogs, negotiate handles agent spending, previewOutfit visualizes combinations, and requestMerge initiates the final action. No two tools overlap in their core purpose.
Most names follow a camelCase verb_noun pattern (listBodies, listItems, previewOutfit, requestMerge), but greet and negotiate are single verbs without a noun object. This is a minor deviation that doesn't create confusion.
Six tools is well-scoped for the server's purpose of browsing, previewing, and merging agent bodies. Each tool contributes a distinct capability without redundancy or bloat.
The core workflow is covered: browse bodies, check items, negotiate, preview, and request merge. Missing operations like checking merge status or cancelling a request are minor gaps that agents can work around, but they are not fatal.