Sakura Forecast Now

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

Annotations already provide readOnlyHint and idempotentHint, confirming safe, idempotent read operations. The description adds value by specifying returned content: concise current answer, viewing spot suggestions, and next-step guidance. No contradiction.

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 a single paragraph containing essential usage instructions. It is concise but could benefit from bullet points or clearer separation of examples and exclusions. Still, no wasted sentences.

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 no output schema, the description adequately explains the return value (concise answer, spot suggestions, next-step guidance). For a simple query tool with three optional parameters, this is sufficient to guide an agent.

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 baseline 3. The description does not add significant meaning beyond the schema; it mentions city and trip dates but the schema already describes them adequately.

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 identifies the tool as handling broad cherry blossom queries like 'How is the sakura forecast?' and specifies it returns a concise current answer from live data. It distinguishes from siblings by targeting 'now' queries and specific examples.

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?

Explicitly states 'Use this first for broad cherry blossom prompts' and lists example queries. Also clearly excludes non-relevant topics like autumn leaves, hotels, and itineraries, providing clear when-to-use and when-not-to-use guidance.

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