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perwinroth

got-cosy-mcp

by perwinroth

find_cosy_hotels

Find independent hotels with a cosy score of 5.0 or higher from Got Cosy's index, filterable by city, country, and minimum score.

Instructions

Find live, cosy-scored hotels from Got Cosy's cosiness index (gotcosy.com): hotels scored 0-10 for warmth, intimacy and character from photos and reviews. Only returns hotels that clear the public floor (score 5.0+). Optionally filter by city, country and a minimum cosy score.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNoCity name, e.g. "Paris"
limitNoMax results (default 20, max 100)
countryNoCountry name, e.g. "France"
min_scoreNoMinimum cosy score 0-10 (the public floor is 5.0 regardless of this value)
Behavior3/5

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 transparently mentions the non-obvious public floor of 5.0 and the live, index-derived scoring context. However, it does not describe the return format, pagination, or any side effects, leaving some behavioral gaps typical for a search tool.

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 sentences long, front-loaded with the core purpose, and every clause adds value (source, scoring, floor, filters). There is no redundancy or filler, making it highly concise and well-structured.

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

Completeness4/5

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

Given the absence of an output schema and annotations, the description covers the essential aspects: what it finds, the source, score floor, and optional filters. It implies the return of a list of hotels but does not explicitly detail the return structure, which would elevate it to a 5.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds meaningful context beyond the schema by clarifying that the public floor of 5.0 applies regardless of min_score and emphasizing the live nature of the data, which enriches the semantics of the parameters.

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 clearly states the tool 'finds live, cosy-scored hotels' from a specific index, with a defined scoring scale and a public floor, effectively distinguishing it from the sibling tool get_hotel_feeling which presumably focuses on individual hotel feelings. The verb 'find' plus resource 'hotels' makes 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?

It provides clear context for use by explaining the data source, the scoring scale, and optional filters (city, country, min_score). However, it does not explicitly state when to use this tool versus alternatives or when not to use it, lacking exclusionary guidance present in a score-5 description.

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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