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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so safety is covered. The description adds meaningful context beyond that: the data is refreshed on a daily cadence and a null current position specifically means 'not in the checked results', which prevents an agent from misreading nulls as a data error.

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?

It is a single, front-loaded sentence that leads with the resource and then lists the returned fields with no filler. The comma-chained field list is slightly dense, but every clause (daily check, null semantics, best-ever, volume) carries information an agent would otherwise have to infer.

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?

This is a small read-only list tool with an output schema and full parameter documentation, so the description does not need to explain return shapes — yet it usefully does so anyway alongside the null caveat. The only missing piece an agent might want is pagination/daily-freshness guidance relative to gsc__performance, which is minor.

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 description coverage is 100%, so limit, offset and workspace_id are already fully documented in the schema ('Max rows, 1-100', 'Keep paging while has_more is true', 'From workspace__list'). The description adds no additional parameter meaning, so the baseline of 3 applies.

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 names the specific resource (Google positions of tracked keywords for a workspace) and enumerates the returned measures (current position, best-ever position, ranking URL, search volume), so an agent knows exactly what comes back. It is not a verb-led statement and it never mentions how it differs from the adjacent gsc__performance or visibility__overview tools, so it stops short of a 5.

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?

Usage is implied rather than stated: 'the keywords this workspace tracks (checked daily)' signals this is the per-workspace tracked-ranking view, and the required workspace_id narrows the context. There is no explicit when-to-use, no when-not-to-use, and no routing to a sibling such as gsc__performance for non-tracked queries.

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