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

With no annotations, the description carries the full burden and does well: it discloses the hourly cache vs live re-pull, the 3-credit cost, that data is public and may lag, and the important caveat that results show reported incidents, not guilt. It omits auth/rate-limit details but covers the operationally relevant traits.

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 dense paragraph that front-loads the core purpose and layer list before filters and cost. The long layer enumeration is necessary for discovery, though it makes the sentence heavy. Little waste overall.

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 15-parameter tool with no output schema and no annotations, the description covers purpose, filters, caching, cost, and return shape ('points plus ranked hotspots'). It leaves a few parameters (limit, radius_miles, state, year) unexplained, which is the main residual 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 description coverage is only 47% across 15 parameters. The description compensates for some (layer vs layers, date range, keyword, map box, refresh) but says nothing about limit, radius_miles, year, state, or near, leaving those to a sparse schema. Partial compensation justifies a 3.

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 a specific verb ('Query public open data') and enumerates the exact resources/layers available. An agent can immediately distinguish this from siblings like crime_stats or crime_case_report because it specifies the layer-based query model and lists the datasets.

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?

It clearly explains when to use `layer` (one dataset) vs `layers` (several at once) and outlines filter mechanics (date range, keyword, map box) plus when to set refresh=true. It lacks explicit guidance distinguishing it from the sibling crime tools, so it stops short of a 5.

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