Apply a proposed clustering

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

Goes well beyond the annotations: it discloses the concrete side effects (clusters created, queries reassigned), the name lower-casing rule, and the collision behavior (an existing matching name is reused rather than duplicated). It also explains the retry safety mechanism via requestId, which is meaningful context given idempotentHint=false.

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?

Four sentences, effectively front-loaded, with the primary effect stated first and safety/naming caveats after. Slightly dense but every clause carries distinct information; nothing is redundant with the annotations or schema.

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 non-idempotent mutation with no output schema, the description covers the lifecycle (propose via start_auto_clustering, preview via get_job, then apply), side effects, and retry semantics. It does not state whether the operation is reversible or what the call returns, which are the remaining 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 only 25%, so the description must compensate, and it does for the most ambiguous parameter: requestId is explained as a fresh idempotency key to reuse only on retry. jobId is contextualized through the 'completed start_auto_clustering job' flow, though organizationId and projectId are left to the schema.

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 precise verb and resource ('Apply the grouping a completed start_auto_clustering job proposed') and immediately enumerates the effects: creates named clusters and moves tracked queries. It is clearly distinguishable from start_auto_clustering (which proposes) and create_clusters (which it references for naming behavior).

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 the precondition (a completed start_auto_clustering job), a workflow instruction ('Show the proposal (get_job) to the user first'), and explicitly routes naming behavior to create_clusters. The alternative tools in the same flow are named, so an agent knows when to reach for this versus them.

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