list_coverage_gaps

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

No annotations are provided, so the description carries the full burden of explaining behavior. It clearly indicates this is a listing operation (no side effects implied) and adds semantic context about candidates and usage ranking. However, it does not disclose details like return format, whether results are ordered, or any permissions needed. The description is adequate but lacks rich behavioral disclosure.

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 two sentences long, front-loaded with the core definition, and ends with actionable usage guidance. Every word earns its place, with no redundancy or filler. It is a model of concise, structured communication.

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?

Given no output schema and no annotations, the description covers the main contextual needs: purpose, use case, and ranking strategy. It could be more complete by describing the output structure or default behavior, but the combination of the purpose statement and usage guidance provides a solid understanding for agent selection. The clarity of the tool's place in the workflow compensates for minor omissions.

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 schema already documents 'limit' and 'offset' with descriptions, but the 'kind' parameter has no description. The tool description adds no parameter-specific meaning and does not mention that you can filter by entity type. While the enum values are self-explanatory, the description misses the opportunity to clarify the role of 'kind' in the context of coverage gaps, leaving the parameter semantics under-specified.

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 clearly states it lists 'Entities NOT measured by any concept' and frames them as 'candidates for new business definitions.' This specific verb-resource pairing distinguishes it from sibling tools like get_concept or lookup_ontology, which handle existing concepts or maps. The purpose is immediately clear and non-tautological.

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 description provides explicit guidance on how to use the results: 'Join with usage data from the Pendo MCP server (e.g. entityUsage) to rank' and identifies high-usage unmeasured entities as strongest candidates. This gives a clear use case and workflow, though it does not name alternatives or explicitly say when not to use this tool. Still, the context is strong enough for an agent to decide appropriately.

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