search-stations

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the search functionality and input types, but lacks details about response format, error handling, performance characteristics, or any limitations beyond the query examples. The description doesn't contradict any annotations (none exist), but could provide more complete behavioral context.

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 efficiently structured in two sentences: the first establishes the core functionality and supported input types, the second provides concrete usage examples. Every element serves a purpose with no wasted words, making it easy to parse while conveying essential information.

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 search tool with no annotations and no output schema, the description provides adequate but incomplete context. It covers the purpose and usage well, but lacks information about what the search returns (station details, codes, locations?), how results are ordered, or any limitations beyond the parameter constraints. Given the tool's relative simplicity and good schema coverage, this is minimally adequate but could be more 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?

The schema description coverage is 100%, so the schema already fully documents both parameters. The description mentions the types of queries supported (Chinese name, pinyin, abbreviation, code) which aligns with the schema's description of the query parameter, but doesn't add significant semantic value beyond what the structured schema provides. The baseline of 3 is appropriate given the comprehensive schema coverage.

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 the tool's purpose as '智能车站搜索' (intelligent station search) and specifies the types of inputs it supports (Chinese name, pinyin, abbreviation, three-letter code). It distinguishes itself from siblings by focusing on station search rather than train or ticket operations. However, it doesn't explicitly contrast with specific sibling tools like 'get-train-route-stations' which might also involve station data.

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 provides clear usage context with examples for both fuzzy search (e.g., '北京') and exact code lookup (e.g., 'BJP'), helping users understand when to apply different query strategies. It implicitly suggests this tool is for station information retrieval, but doesn't explicitly state when to use alternatives like 'query-tickets' or 'get-train-route-stations' for related but different purposes.

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