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

Annotations already declare readOnly/idempotent/non-destructive, so the description doesn't need to restate that. It adds meaningful behavioral context: the tool requires Google Search Console to be connected and directs the user to a specific integration URL. It also clarifies the daily granularity of the trend data.

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?

Three sentences, front-loaded with the core function, followed by use case and prerequisite. Every sentence earns its place; no fluff or redundancy.

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 tool with no output schema and four required parameters, the description adequately covers what data is returned (clicks/impressions/CTR/position) and the prerequisite (GSC connection). It's not exhaustive regarding pagination or aggregation details, but sufficient for an agent to invoke it correctly.

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?

Input schema covers 100% of parameters with descriptions (page, site, startDate, endDate). The description adds no additional parameter-level semantics beyond what the schema already provides; the baseline of 3 applies since schema does the heavy lifting.

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+resource: 'Get daily click/impression/CTR/position trend for a specific page.' This clearly distinguishes it from sibling tools like get_gsc_query_trend (query-focused) and get_gsc_date_trends (site-wide) by explicitly stating the scope is a single page.

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 states when to use: 'to see how a single page's search performance has changed over time, useful for measuring the impact of a content update or spotting a ranking drop.' This is clear usage context, though it does not explicitly name alternative tools for negative guidance. The integration prerequisite adds useful context.

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