agriculture-mcp-server

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

Discloses data source (World Bank) which is valuable behavioral context given no annotations, but omits error handling, data freshness, or rate limit information.

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?

Extremely concise with no fluff; front-loaded purpose followed by data specifics, source attribution, and parameter definition.

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?

Adequately covers the simple single-parameter input and compensates for missing output schema by enumerating returned data categories.

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?

Excellently compensates for 0% schema description coverage by specifying the ISO3 format and providing concrete examples (DEU, USA, BRA, IND, CHN).

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 comprehensive agricultural profiles listing specific metrics (yields, land use, GDP share) that distinguish it from weather-focused siblings like climate_averages and product-focused food_search.

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?

Provides no explicit guidance on when to use versus alternatives (e.g., when to use this instead of crop_weather_forecast for agricultural planning).

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