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

Annotations already declare readOnly, idempotent and non-destructive, so the safety profile is covered. The description adds genuinely useful behavior beyond that: results are truncated to the top N rows and columns ranked by the first metric, the total counts are reported, and totals are appended. That truncation/ranking behavior is exactly the kind of thing an agent needs and cannot get from the schema.

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?

One dense sentence, front-loaded with the resource and scope, then the output shape, then the truncation rules. Every clause carries information, though the single-sentence run-on makes the limits and totals rules slightly harder to scan than a short bulleted structure would.

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?

With an output schema present, return values need not be described, and the description still covers the non-obvious parts: truncation, ranking metric, total counts and totals. For a 9-parameter read-only report tool this is sufficient to call 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?

Schema coverage is only 22%, so the description has to carry the load, and it does: it gives the property format (properties/<id>), the date-range role of start_date/end_date, the meaning of rows/columns/metrics, and the caps on row_limit (100) and column_limit (25) plus the default totals behavior. It does not say where valid dimension and metric names come from (e.g., ga4_get_metadata), which is the remaining gap.

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 a specific verb and resource ('Cross-tab for a GA4 property') and defines the shape of the output (rows down the side, columns across, metrics in cells), which clearly separates it from ga4_run_report, ga4_run_cohort_report and ga4_run_funnel_report. It stops short of naming those siblings explicitly, so it is clear but not fully differentiated.

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 only implied: the cross-tab framing suggests when a pivot is preferable to a flat report, but there is no explicit 'use this instead of ga4_run_report when...' statement and no prerequisites or exclusions. An agent must infer the choice from the shape description.

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