blv_get_meat_inspection_stats

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

Annotations already indicate readOnlyHint, idempotentHint, and openWorldHint. The description adds behavioral detail by naming the specific outputs (slaughter counts and condemnation rates), which helps the agent understand what data to expect without needing to parse the output schema.

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 two sentences long, front-loading the tool's purpose and immediately following with a concrete use case. Every sentence adds value, no redundant text.

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 low complexity (2 optional parameters) and the presence of an output schema and comprehensive annotations, the description is complete enough for an agent to understand the tool's role and retrieve the expected data. The only minor gap is absence of example values for year or animal_type.

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?

With 100% schema coverage, the schema already documents both parameters (year and animal_type). The description merely echoes these in its use case, adding no extra meaning beyond what the schema provides. A score of 3 is appropriate as the baseline.

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 identifies the tool as providing slaughterhouse meat inspection statistics, specifying 'slaughter counts and condemnation rates by animal type and year.' This distinguishes it from sibling tools like blv_get_animal_health_stats or blv_get_antibiotic_usage_vet, which focus on different 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 states the use case as reviewing slaughter counts and condemnation rates, giving clear context for when to use the tool. However, it does not explicitly mention when not to use it or suggest alternative tools for non-matching queries.

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