get_hate_crime_data

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

Without annotations, the description carries full burden. It discloses conditional parameter dependencies (e.g., state required when level is 'state') and explains default behaviors (aggregate='yearly', data_type='counts'). However, it does not mention read-only status, rate limits, authentication requirements, or any side effects, which are important for an agent to use safely.

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 well-structured as a docstring with a brief overview followed by a clean parameter list. Each sentence serves a purpose, though the parameter list could be slightly streamlined. Overall, it is efficient and front-loaded.

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 complexity (8 parameters, 3 required) and the presence of an output schema, the description covers parameter semantics thoroughly. It lacks only a sample usage or mention of error conditions, but remains complete enough for an agent to invoke the tool correctly.

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 0%, so the description must fully compensate. It explains every parameter: format (mm-yyyy for dates), allowed values (e.g., 'national','state','agency' for level), defaults, and conditional requirements. It even references another tool for bias code lookup, adding significant value beyond the schema.

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 hate crime statistics with optional bias filtering, and lists the types of data returned (incident counts, victim types, etc.). It distinguishes itself from sibling tools by focusing specifically on hate crime data, which is unique among the listed 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?

The description provides detailed guidance on parameter usage, such as conditional requirements for state and ori depending on level, and the difference between data_type and aggregate options. However, it does not explicitly compare this tool to alternatives like get_arrest_data or get_nibrs_data, leaving the agent to infer when to use this over others.

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