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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds valuable behavioral context: it discloses the source (USDA Livestock Mandatory Price Reporting Datamart), the public-domain license, publication frequency, and the regional scope. This goes beyond the annotations without contradicting them.

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 three sentences with no redundancy. It front-loads the core purpose and data content, then covers coverage, frequency, and source efficiently. Every sentence earns its place.

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?

With an output schema present and full parameter documentation in the schema, the description adequately covers the data content, geographic coverage, frequency, and source. It is sufficiently complete for an agent to correctly call the tool, though it could optionally mention that omitting report_date retrieves the latest report (already covered in the schema).

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% and both parameters have detailed descriptions in the schema (format for report_date, default and effect of all_sections). The tool description does not add any parameter-specific meaning beyond what the schema already provides, so the baseline score of 3 is appropriate.

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 states a specific verb ('Returns') and resource ('5-Area daily weighted-average direct slaughter cattle prices'), listing concrete outputs (head counts, price ranges, weighted averages) and clearly distinguishing the tool from siblings like lmpr.hog.slaughter_prices by naming 'cattle' and the LM_CT100 report.

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 does not explicitly state when to use this tool over alternatives. It notes publication frequency ('Published daily on USDA business days') and geographic coverage, but provides no direct contrast or selection criteria for when an agent should pick this versus sibling tools like lmpr.hog.slaughter_prices. Usage context is implied but not made explicit.

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