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

Annotations already establish read-only, idempotent, and non-destructive behavior, and the description adds meaningful context beyond them: it identifies the data source as official Japanese Government open data and explicitly states no auth is required. It also explains the Shindo scale, which helps an agent interpret the intensity values in the response.

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 front-loaded with the core purpose, then covers returned fields, filtering, scale interpretation, the sibling relationship, and data source/auth in a compact sequence. Each sentence earns its place and there is no filler.

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?

This is a low-complexity read-only tool with two optional parameters and an output schema, and the description covers everything an agent needs to select and invoke it correctly: source, return fields, filtering option, scale meaning, alternative feed, and authentication status. The only issue is the slightly inaccurate sibling name reference, which is more a usage-guideline concern than a completeness gap.

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%, so the input schema already documents limit and min_magnitude well. The description's mention of filtering by minimum magnitude reinforces the schema but adds little new semantic information beyond it, 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 opening sentence names a specific verb ('Get'), resource ('most recent earthquakes'), and authoritative source (the Japan Meteorological Agency). It then enumerates the returned fields, which makes the tool's scope concrete. It also positions itself against the community p2pquake feed, helping an agent distinguish it from earthquake-related siblings.

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 explicitly names a complementary alternative ('p2pquake.seismic.recent') and contrasts it as a community network versus the official government feed, giving clear selection context. It lacks explicit when-not-to-use phrasing, and the named sibling does not exactly match the actual sibling list entry 'p2pquake.seismic.recent_quakes', which prevents a perfect score.

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