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search_stops

Find Prague public transit stops by name with flexible case and diacritics handling. Use results to query departures and other city data.

Instructions

Search for Prague public transit stops by name.

Args:
    name: Stop name to search for (case-insensitive, diacritics-insensitive).
          Examples: "Letňany", "Letnany", "mustek", "Můstek" all work.
    limit: Maximum number of results (default: 10)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the behavioral burden. It discloses useful traits: case-insensitive and diacritics-insensitive matching, and a default limit. While it does not explicitly state read-only or side-effect-free, 'search' implies a safe, non-mutating operation. The details go beyond what is obvious from the tool name.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short sentences plus a compact Args block. Every sentence adds value: first sentence states purpose, Args block clarifies parameters with examples. There is no filler or repetition, and the format is easy to scan.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (2 params, output schema provided), the description is complete. It covers the search scope, parameter behavior, and examples. Return values are handled by the output schema, so no additional explanation is needed. The tool is small, and no context is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage, so the description fully compensates. It explains the 'name' parameter with matching semantics and provides concrete examples ('Letňany', 'Letnany', 'mustek'). It also documents the 'limit' parameter's default value. This is far beyond what the bare schema offers.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'Search' and clearly identifies the resource ('Prague public transit stops by name'). This distinguishes it from sibling tools like get_departures or get_city_districts, which are either retrieval or unrelated, making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use the tool: when you need to find a stop by name. It does not explicitly mention alternatives or when-not-to-use, but the purpose is so distinct from siblings that the guidance is effective. No exclusions are necessary here.

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

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