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

Beyond the annotations (read-only, idempotent), the description discloses the status enum (normal/delayed/suspended/resumed), how cause text is handled (English summary for known patterns, else original text + null), and credits ODPT as the data source with license. This adds real behavioral detail without contradicting annotations.

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?

Four concise sentences packed with relevant information — purpose, usage, enum, data source. No filler words. Front-loaded with the most important part.

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?

The tool has a single query parameter, a read-only action, and an output schema. The description covers purpose, usage, result format (status enum and cause handling), and data provenance. There's no gap that would hinder an agent from using it correctly.

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?

The input schema already documents query as 'Line or station name (English or Japanese)'. The description repeats this and adds an example query. With 100% schema coverage, the baseline is 3; the description adds minimal extra semantic meaning beyond the schema, so 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 description opens with 'Live train service status for Tokyo-area lines' — a specific verb (get status), resource (Tokyo-area train lines), and scope (delays, suspensions, resumptions). It clearly distinguishes from sibling tools like get_station_alerts or station_search by focusing on line-level running status rather than station facilities or alerts. The example phrasing solidifies 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?

It gives concrete usage context (ask by line or station name, English or Japanese) and a natural-language example ('is the Yamanote Line running?'). It does not explicitly name alternatives or exclusions, so it earns 4 rather than 5. The context alone makes it clear when to use it.

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