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

The annotations already declare idlempotentHint=true, readOnlyHint=false, and destructiveHint=false, so the safety profile is covered. The description adds genuinely non-obvious async behavior — that this queues a hosted job rather than returning inline — which is exactly the kind of trait annotations cannot express.

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?

Two sentences, zero filler, and the primary action is front-loaded ahead of the async note. Every clause earns its place.

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 mutating, job-queuing tool with no output schema, the description covers the essentials: what it produces and how the result is retrieved via get_job. Only the undocumented idempotencyKey and the lack of sibling-selection guidance leave minor gaps.

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 75%, so most parameters (uploadId, requestId, workspaceToken) are documented in the schema itself and the description adds nothing beyond them. The one uncovered parameter, idempotencyKey, is left undocumented in both the schema and the description, so baseline 3 is appropriate.

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?

States a specific verb (import) and resource (a full-data Crosstabs project package) plus the outcome (as a new workspace copy), which distinguishes it implicitly from import_dataset and create_project. It is clear and actionable without needing to open the schema.

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?

It gives one explicit routing cue — 'use get_job to retrieve its result' — which sets up the async workflow correctly. However, it never says when to choose this over siblings like import_dataset, create_project, or create_workspace, so the selection guidance is only partially covered.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.