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

Annotations already declare readOnlyHint true and destructiveHint false, and the description reinforces that with 'Read-only, free.' More importantly, it explains the meaning of like_for_like (true/false/null) and warns never to present a delta as a result when like_for_like isn't true, adding significant interpretive context beyond the 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?

The description is moderately long but well-structured: it starts with a framing question, lists the report contents, then gives the essential like_for_like rule. Each sentence earns its place, though the like_for_like explanation is somewhat verbose.

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 read-only tool with one parameter and no output schema, the description provides a solid mental model of what the return includes (visibility at both ends, moves, scans, receipts) and how to interpret the key field. It doesn't describe exact output formatting, but that's not essential for an overview tool with good annotations.

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?

The single parameter window_days is fully documented in the schema (range, default, clamping behavior) with 100% schema coverage, so the description doesn't need to repeat it. The description adds no parameter-specific semantics beyond the schema, but the schema itself is sufficiently complete.

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 'Did the growth work move anything?' and clearly defines the resource as a proof read covering AI visibility at start/end of the window, moves shipped, scans, and receipts. This makes it a distinct period-over-period growth scoreboard, easily distinguishable from siblings like get_visibility or get_outcomes.

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 use case is implied through the framing question and the detailed like_for_like caution, but the description doesn't explicitly name alternatives or state when not to use this tool. It gives clear context for interpretation after calling, but lacks direct guidance on tool selection relative to siblings.

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