Agriculture triangle: crop drought ($0.10)

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

No annotations provided, so description must cover behavioral traits. It discloses cost ($0.10 USDC on Base), data sources (NOAA satellite VHI, USDM), and the four analytical components. However, it does not describe the output format, rate limits, or authentication requirements, leaving some ambiguity about how the tool behaves at runtime.

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 concise (2-3 sentences), front-loads the core purpose, and includes essential details (cost, data sources, examples) without unnecessary words. Every sentence adds value.

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 tool's complexity (four analytical components) and lack of output schema, the description provides a good overview of what the tool returns (soil moisture, heat/GDD, vegetation health, cross-validation). However, it could improve by explicitly describing the output format (e.g., numeric indices, categorical status) and any prerequisites for use (e.g., API key).

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 the parameter 'loc' is described with examples ('us-iowa, ar-pampas, ua-ukraine') both in the schema and the main description. The description adds real-world context by listing grain region examples, which helps the agent understand valid inputs 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?

Description clearly states it gauges agricultural drought for a grain region, listing four specific data components (soil moisture, heat/GDD, vegetation health, cross-validation). Distinguishes from sibling tools like gauge_flood_risk or gauge_grid_stress by focusing on crop-specific drought analysis. Verb is implicit in 'gauge' and the title 'Agriculture triangle: crop drought' reinforces the purpose.

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?

Target audience ('For ag traders & crop insurers') is explicitly mentioned, and the description implies usage for monitoring drought impact on crops. However, no explicit guidance on when not to use this tool or how it compares to siblings like gauge_flood_risk or gauge_river_free, which might also be relevant for agricultural analysis.

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