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

Annotations cover the safety profile (readOnly=false, idempotentHint=true, destructiveHint=false), and the description adds the important asynchronous behavior beyond that: a job is queued and must be polled via get_job. It does not say what happens on validation failure, whether a partial import can occur, or how validation errors surface.

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 short sentences, zero filler, with the operation and its follow-up action front-loaded. Every sentence 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?

There is no output schema, and the description reasonably covers retrieval of results via get_job, so the return path is handled. However, for a 6-required-parameter mutation tool, the semantics of expectedRevision and idempotencyKey and the failure behavior of validation are left undocumented.

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 description mentions no parameters at all, and schema coverage is only 50% — uploadId, requestId, and workspaceToken are documented in the schema, but projectId, idempotencyKey, and expectedRevision (apparently an optimistic-concurrency revision guard) are unexplained in both places. With a mutation tool carrying an expectedRevision and idempotencyKey, the description should have compensated for that gap and did not.

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-plus-resource ('Validate and import respondent records into a project wave'), which is clear on its own. It does not explicitly distinguish itself from close siblings such as import_project or replace_dataset, so the agent must infer the boundary from names alone.

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?

Gives a concrete next-step routing rule: the call queues a hosted job and the agent should call get_job for the result. That is genuine usage guidance, but there is no statement of when not to use this tool versus import_project/replace_dataset.

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