Field usage

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

Annotations already declare readOnly, idempotent, non-destructive and open-world, so the safety profile is covered. The description adds only that it returns 'usage figures for this field' — marginally useful context about the nature of the result (population density rather than values), but no detail on shape, cardinality, or cost of the open-world lookup.

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 labeled sections (Purpose / Not for / Returns / Use when) with one sentence each; the key differentiator and the alternative tool are front-loaded and no sentence is redundant.

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-parameter read tool with no output schema, the description covers purpose, exclusion, return nature and decision context adequately. It stops short of describing the returned figures (counts vs. percentages, per-contact breakdown), which is the only remaining gap.

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% with a single documented 'field' parameter, so the schema carries the semantics. The description's references to 'a custom field' and 'this field' add nothing beyond what the schema already states.

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?

States a specific verb+resource ('Report how widely a custom field is populated across contacts') and explicitly names the sibling it is not (plunk_get_field_values), so an agent can distinguish the two without opening either schema.

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 when' block names two concrete decision contexts (whether a field is worth segmenting on, or safe to delete), and 'Not for' routes away the adjacent tool. Both when-to-use and when-not-to-use are explicit.

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