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

Annotations already mark the tool as non-readOnly, idempotent, and non-destructive. The description adds valuable behavioral context: it rebuilds specific rollups and page rows, is free, and will not produce fresher data beyond Google's 2-3 day lag. No contradiction with annotations.

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 focused sentences, each earning its place: the action, the cost, the existing daily cadence, and the upstream data limitation. The core purpose is front-loaded, and there is no filler or repetition.

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 single-optional-parameter sync tool with no output schema, the description covers the trigger, side effects, cost, freshness constraints, and relationship to the existing scheduled job. An agent has enough context to select and invoke it correctly without further inference.

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 100%, and the single optional workspaceId parameter is already documented in the schema, including the distinction between user keys and workspace keys. The description adds no parameter-specific detail, but none is needed given the schema's completeness.

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?

The description opens with a specific verb ('Pull') and resource ('fresh Search Console data'), then names the concrete outputs ('28-day query rollups' and 'long-history page rows'). This clearly distinguishes it from the many getter/list sibling tools by framing it as an active sync operation.

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?

The description explicitly tells the agent when to use it: when data newer than the last sync is needed, not on every read. It also explains that a daily job already handles this and that Google lags 2-3 days, giving strong, actionable context for deciding whether invoking this tool is worthwhile.

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