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get_workspace

Retrieve company information, offerings, and knowledge schema overview to understand available data in the workspace.

Instructions

Get workspace company info, offerings, and knowledge schema overview. Returns company details (name, industry, size, offerings) and a summary of all knowledge lists with their field definitions and row counts. Use this as a first call to understand what data the workspace has.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Registration of the 'get_workspace' MCP tool, including its handler logic which delegates to client.getWorkspace().
        server.tool(
            'get_workspace',
            `Get workspace company info, offerings, and knowledge schema overview.
    Returns company details (name, industry, size, offerings) and a summary of all knowledge lists with their field definitions and row counts.
    Use this as a first call to understand what data the workspace has.`,
            {},
            async (_args, extra) => {
                const client = clientFactory(extra);
                const result = await client.getWorkspace();
                return {
                    content: [{
                        type: 'text' as const,
                        text: JSON.stringify(result, null, 2),
                    }],
                };
            }
        );
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes what information is returned (company details and knowledge list summaries) but doesn't mention potential limitations like rate limits, authentication requirements, or whether this is a read-only operation. It adequately describes the scope but lacks operational context.

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

Conciseness5/5

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

The description is perfectly concise with three sentences that each serve a distinct purpose: stating what the tool does, detailing what it returns, and providing usage guidance. There's zero wasted language, and the information is front-loaded appropriately.

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 this is a 0-parameter tool with no annotations and no output schema, the description does a good job explaining what the tool returns and when to use it. However, without an output schema, the description could benefit from more detail about the exact structure of the returned data (beyond just listing categories).

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 tool has 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and it focuses on the tool's purpose and usage instead.

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: 'Get workspace company info, offerings, and knowledge schema overview' with specific details about what information is returned. It distinguishes from siblings by focusing on workspace metadata rather than operations like 'get_knowledge_rows' or 'list_workflows', though it doesn't explicitly name alternatives.

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

Usage Guidelines5/5

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

The description provides explicit usage guidance: 'Use this as a first call to understand what data the workspace has.' This clearly indicates when to use this tool versus alternatives, positioning it as an initial discovery/exploration tool before diving into specific data operations.

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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