get_popular_labels

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

With no annotations present, the description carries the behavioral disclosure burden. It transparently explains the sort criterion (node degree), the ordering direction (most-connected first), and the intended interpretation of 'popular.' It does not cover edge cases like isolated labels or exact count semantics, but the core behavior is clearly disclosed.

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 a single well-structured sentence that front-loads the key sorting behavior and follows it with a concise, useful rationale. There is no redundant filler or excessive length.

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 the tool's low complexity (one optional parameter, full schema coverage, and an output schema present), the description is largely sufficient for an agent to select and invoke it correctly. It could add an explicit pointer to sibling tools or mention response shape, but the output schema compensates for the latter.

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 fully documents the only parameter, limit, including its default, range, and meaning. The description does not add parameter-specific details beyond what the schema already provides, so the baseline 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 states a specific verb ('List') and resource ('entity labels'), and clarifies the distinguishing behavior: sorting by node degree, most-connected first. It clearly signals a popularity-oriented view rather than generic label listing, though it does not explicitly name sibling alternatives.

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 phrase 'a quick way to see what the knowledge graph is mostly about' implies an overview/summary use case. However, it does not explicitly contrast with related sibling tools like get_graph_labels or search_labels, nor does it say when not to use this tool.

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