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rspace-os

RSpace MCP Server

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by rspace-os

get_workbenches

Retrieve available workbenches (virtual workspaces) to organize and access research data containers in RSpace.

Instructions

Retrieves all available workbenches (virtual workspaces)

Usage: Find available workspaces for organizing current work Workbenches: Special containers representing physical or logical workspaces Returns: List of all workbench containers

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • main.py:959-969 (handler)
    MCP tool handler function for 'get_workbenches'. Decorated with @mcp.tool for automatic registration. Executes the tool logic by delegating to inv_cli.get_workbenches(), which retrieves all workbench containers.
    @mcp.tool(tags={"rspace", "inventory", "containers"})
    def get_workbenches() -> List[dict]:
        """
        Retrieves all available workbenches (virtual workspaces)
        
        Usage: Find available workspaces for organizing current work
        Workbenches: Special containers representing physical or logical workspaces
        Returns: List of all workbench containers
        """
        return inv_cli.get_workbenches()
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses that the tool retrieves 'all available workbenches' and returns a 'List of all workbench containers,' indicating it's a read-only list operation. However, it doesn't mention behavioral traits like pagination, rate limits, authentication needs, or error handling, leaving gaps for a tool with no annotation coverage.

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 structured into three clear sentences: purpose, usage, and return value. It's front-loaded with the main action and avoids redundancy. However, the second sentence ('Workbenches: Special containers...') could be integrated more smoothly, and there's minor room for tightening without losing clarity.

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?

Given the tool's simplicity (0 parameters, no annotations, but has an output schema), the description is reasonably complete. It explains what the tool does, when to use it, and what it returns. The output schema likely covers return values, so the description doesn't need to detail them further. It could improve by addressing sibling differentiation or behavioral aspects like error cases.

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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate. A baseline of 4 is applied as it compensates adequately for the lack of parameters by focusing on the tool's purpose and output.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Retrieves all available workbenches (virtual workspaces)' with a specific verb ('Retrieves') and resource ('workbenches'). It distinguishes workbenches as 'Special containers representing physical or logical workspaces,' which helps differentiate from generic container tools like 'list_containers' or 'get_container,' though it doesn't explicitly name those siblings.

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 description provides implied usage guidance: 'Usage: Find available workspaces for organizing current work' suggests when to use it (for workspace discovery and organization). However, it lacks explicit alternatives or exclusions, such as when to use other container-related tools like 'list_containers' or 'get_container,' which are siblings.

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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