get_crime_trends

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

No annotations are provided, so the description bears full responsibility for disclosing behavior. It states that the tool returns percent changes across crime types but omits important details such as potential caching, rate limits, error handling for out-of-range years, or whether the data represents year-over-year changes. For a tool with no annotations, this is insufficient 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 concise, consisting of a main sentence and an 'Args' section that lists parameters. It front-loads the key purpose and enumerates the crime types. The addition of the 'Args' section is slightly redundant with the schema but adds clarity. Every sentence is useful, though the structure could be more streamlined.

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?

The tool has only two optional parameters and an output schema exists, so the description need not explain return values. However, the description omits details on how the percent changes are computed (e.g., over the entire range or year-over-year) and does not address edge cases like missing data for certain years. Given the complexity of crime trend data, the description is minimally adequate but not comprehensive.

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 has 0% description coverage, meaning the description must compensate. The description adds meaning by specifying that from_year and to_year are optional, use 'yyyy' format, and represent start and end years. This goes beyond the schema's type and default values, providing clear usage intent for both parameters.

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 that the tool retrieves national crime trend data showing percent changes across 10 specific crime types. It uses a specific verb ('Get') and resource ('national crime trend data'), and the list of crime types distinguishes it from sibling tools that focus on specific subsets (e.g., NIBRS data, hate crime data).

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 parameter hints (optional from_year and to_year with format) but no guidance on when to use this tool versus siblings, nor any exclusions or prerequisites. For example, it does not explain that this tool is for national-level trends while other tools like 'get_summarized_crime_data' may provide different aggregations. This lack of context makes it harder for an agent to decide when to invoke this tool.

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