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

With no annotations provided, the description carries the full burden. It discloses that features are GeoJSON Points with name, category, and subtype, that the response is unpaged by default, that large suburbs can be ~3.7 MB, and that count and categories always reflect the whole suburb even when paging. This is substantial transparency about behavior, though it omits error cases or edge conditions.

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 multi-sentence but well-structured and front-loaded: the first sentence states the core output, the second details fields, the third gives use cases, and the remaining sentences cover paging, totals, and pricing. Each sentence adds necessary information without fluff. Slightly long, but every part earns its place.

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 complexity (4 parameters, output schema) and the lack of annotations, the description covers all essential aspects: output format, field semantics, usage patterns, paging behavior, total counts, and cost. Nothing an agent needs to correctly call the tool and interpret results is missing. It even explains how to handle large suburbs.

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 description coverage is 75%, and the description adds meaningful context beyond the schema. It explains the role of 'subtype' and 'category' for filtering/counting, clarifies that 'count' and 'categories' are always whole-suburb regardless of limit/offset, and advises on using limit/offset for large results. This goes beyond the bare schema descriptions, which only state defaults and types.

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 returns 'Every named venue / amenity in the suburb as GeoJSON Point features, plus a per-category count.' It specifies the exact resource (venues/amenities) and verb (returns) and even lists the use cases ('what / how many <venue type> are in this suburb' and 'name the pubs / cafes / gyms in X'). This distinguishes it from siblings like properties_amenities_nearby, which target a different context.

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 explicitly states when to use this endpoint ('This is the endpoint for...') and provides practical guidance on filtering by subtype, counting features, and using limit/offset or category to narrow results. It also gives a performance warning for large suburbs and mentions pricing is flat. It doesn't explicitly name alternatives to avoid, but the usage context is clear enough for an agent to select this tool appropriately.

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