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get_workspace
Read-onlyIdempotent

Call first in every conversation. Returns the authenticated user, every accessible organization with its plan usage, and each organization's namespaces with data source, website-context availability, and lastDataAt (null when no data has arrived) in one call, so the target namespace can be identified without separate discovery calls.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reasonYesA short phrase saying why you are calling this tool, for example: find unpaid invoices.
user_intentYesOne sentence describing what the user is trying to accomplish. Keep it the same across calls until the user's goal changes.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
noticeNo
truncationYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuinely useful behavioral context beyond that: it enumerates what the payload contains and clarifies the null semantics of lastDataAt ('null when no data has arrived'), which prevents misreading an empty namespace as an error.

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?

A single front-loaded sentence opens with the imperative 'Call first in every conversation' before the payload detail, so the most actionable guidance is first. The remainder is dense but long, and the field enumeration edges toward what the output schema already carries.

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?

For a read-only discovery tool with a full output schema, the description covers everything an agent needs: when to call it, what it returns, and the null-value caveat. The return-value enumeration is partly redundant with the output schema, but nothing required is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and both parameters (reason, user_intent) are fully documented in the schema as boilerplate telemetry fields. The description adds no parameter meaning, which is acceptable at this coverage level but earns no credit above the baseline.

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

Purpose5/5

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

States a specific verb and resource ('Returns the authenticated user, every accessible organization... each organization's namespaces') and enumerates the exact fields returned, so an agent can distinguish it from list_organizations, list_namespaces, and get_namespace_overview without opening schemas. The scope ('in one call') makes it clearly the aggregated discovery tool.

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

Usage Guidelines4/5

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

'Call first in every conversation' gives an explicit timing directive, and 'so the target namespace can be identified without separate discovery calls' names the alternative approach it replaces. It stops short of naming specific sibling tools to avoid or stating when-not to call it, so it is strong context rather than a full when/when-not/alternatives matrix.

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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