list_workspaces
Retrieve all Mural workspaces with their IDs and names to identify available spaces for collaboration.
Instructions
List Mural workspaces (stripped to id+name)
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Retrieve all Mural workspaces with their IDs and names to identify available spaces for collaboration.
List Mural workspaces (stripped to id+name)
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 adds value by revealing that the output is limited to 'id+name', which is a behavioral trait. However, it does not explicitly state whether the operation is read-only, mention permissions, or describe any side effects, though 'List' implies a 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that conveys the essential information in just a few words. Every component earns its place: the verb, the resource, and the output shape.
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?
For a simple, parameterless tool with no output schema, this description provides sufficient context: what is listed and the exact fields returned. It is not overly complex, and the description covers the key aspects needed for an agent to select and invoke the 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 input schema has zero parameters, so per the rubric the baseline is 4. The description does not need to explain parameters; it adds output-related context ('stripped to id+name') beyond the schema.
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 clearly states a specific verb 'List' and resource 'Mural workspaces', and further specifies the output shape 'stripped to id+name'. This distinguishes it from sibling tools like list_rooms and list_murals by naming the exact entity being listed.
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 implies the tool is for retrieving workspaces but provides no explicit guidance on when to use it versus alternatives like list_rooms or list_murals. The context is clear (need workspace listing), but there are no exclusions or alternative references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/janschmiedgen/mural-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server