Cherry Blossom Forecast

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

Description discloses returned data (bloom dates, full-bloom dates, observed dates, historical averages, status from Japan Meteorological Corporation) and confirms annotations (readOnlyHint, idempotentHint). No contradictions; description adds valuable context beyond 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?

Two sentences, direct and front-loaded with purpose. No extraneous information; 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?

For a read-only forecast tool with one optional parameter and no output schema, the description sufficiently covers what the tool returns, its source, and its scope. It also provides guidance on related tools, making it contextually complete for the AI 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 coverage is 100% for the single parameter 'city', providing detailed semantics (optional, filter by city/prefecture/region, partial case-insensitive match). Description does not add additional parameter meaning beyond what schema already provides, so baseline 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?

Description clearly states the tool returns cherry blossom forecasts, peak bloom dates, and comparisons across Japan, using specific verbs like 'returns' and naming resources. It distinguishes itself from siblings by noting that it is for observation cities, not specific parks or temples, which aligns with the sibling tools like sakura_spots.

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 when to use (user asks about cherry blossom timing, peak bloom, start, or city comparisons) and when not to use (specific parks/temples, directing to sakura_spots). Provides clear guidance on alternatives.

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