agriculture-mcp-server

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

Discloses data source (NASA POWER) and temporal coverage (ab 1981), but omits other behavioral traits like rate limits, authentication requirements, or return format structure.

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?

Well-structured with front-loaded key information (source, date range, metrics); Args section efficiently documents parameters without redundancy.

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?

Adequate for the tool's low complexity, though absence of output schema could have been mitigated by describing the return structure beyond listing metrics.

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?

Excellent compensation for 0% schema description coverage by providing parameter meanings (German translations) and critical format examples (YYYYMMDD) in the Args section.

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?

Clearly states it retrieves historical agricultural climate data from NASA POWER (since 1981) and lists specific metrics (temperature, precipitation, solar radiation, soil moisture, evapotranspiration); 'historical' distinguishes it from sibling forecast tools.

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?

Mentions implied use cases (site evaluation, climate analysis) but lacks explicit guidance on when to use this versus climate_averages or other siblings.

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