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

Since no annotations are provided, the description carries the transparency burden. It accurately describes what data is returned and its scope, and 'get' implies read-only behavior, but it does not describe the output shape, size implications, or error/edge-case behavior.

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?

A single sentence front-loads the core facts, includes scope and content, and contains no filler. Every clause contributes useful information.

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 two-parameter read-only lookup, the description covers available years, geography, and the aggregate nature of the output, with the 100% schema coverage handling parameter details. It is complete enough, though it stops short of explicitly routing users to alternative tools for other needs.

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 100%, so the schema already explains year and includeIncidents. The description adds aggregate-output context but does not materially enhance the meaning of either parameter beyond what the schema provides.

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 names the resource (full-year VPD crime data), the output type (totals and ranked neighbourhood stats), and hard scope constraints (Vancouver only, 2003-present). This clearly separates it from point-incident or trend-oriented siblings.

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?

Usage is implied through scope constraints: use for Vancouver-only, full-year aggregate crime stats. However, there is no explicit guidance about when to prefer this over siblings like get_incidents or get_trends, and no when-not-to-use conditions are stated.

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