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

With no annotations, the description carries full burden. It discloses output fields but omits info on read-only nature, rate limits, or any side effects. The description is adequate but not rich in behavioral details beyond the obvious.

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?

Two sentences, front-loaded with the core functionality and data sources, followed by use cases. No redundant information, 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?

For a simple tool with 3 optional parameters and no output schema, the description covers the essential return fields and use cases. It is slightly lacking in explaining scope (e.g., global, significant magnitudes) but is largely complete.

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% (each parameter has a description with defaults and ranges). The tool description adds no extra semantics beyond what is already in the schema, so baseline 3 applies.

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 states it returns recent earthquakes from a specific aggregator, lists fields (magnitude, location, depth, time, source), and mentions use cases. However, it does not explicitly distinguish from sibling 'alya_seismic_forecast', though the name implies differentiation.

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?

Explicit use cases are given (real-time monitoring, news, risk assessment, verifying a felt event), providing good context. No exclusions or alternatives are mentioned, but the sibling context implies forecast tool for predictions.

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