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GRABOSM

OpenStreetMap MCP Server

by GRABOSM

search_pois_smart

Find points of interest like restaurants, shops, and tourist attractions using enhanced OpenStreetMap queries with category and location filters.

Instructions

Smart POI search using Taginfo-enhanced queries for restaurants, shops, tourism, etc.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryYesPOI category: "restaurant", "shop", "tourism", "amenity", or specific type
subcategoryNoSubcategory (e.g., cuisine type for restaurants, shop type for shops)
bboxNoBounding box to search within
aroundNoSearch around a specific location
limitNoMaximum number of results (default: 50)
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'Taginfo-enhanced queries' which hints at some intelligence or data enrichment, but doesn't explain what this means operationally—how results differ, whether there are rate limits, authentication needs, or what the output format looks like. For a search tool with 5 parameters and no output schema, this leaves significant behavioral gaps.

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

Conciseness4/5

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

The description is a single, efficient sentence that front-loads the core purpose. It wastes no words, though it could be slightly more informative by elaborating on 'smart' or 'Taginfo-enhanced' without becoming verbose. The structure is clear but minimal.

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

Completeness2/5

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

Given the tool's complexity (5 parameters including nested objects, no output schema, and no annotations), the description is incomplete. It doesn't explain the 'smart' aspect, output format, error handling, or how it differs from similar tools. For a search tool that likely returns structured data, more context is needed to guide effective use.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all 5 parameters thoroughly. The description adds minimal value beyond the schema—it mentions 'restaurants, shops, tourism, etc.' which loosely relates to the 'category' parameter, but doesn't provide additional syntax, format details, or examples. This meets the baseline 3 when schema coverage is high.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Smart POI search using Taginfo-enhanced queries for restaurants, shops, tourism, etc.' It specifies the action (search), resource (POIs), and enhancement method (Taginfo-enhanced). However, it doesn't explicitly differentiate from sibling tools like 'search_pois' or 'search_by_tags', which appears to be a similar POI search tool without the 'smart' enhancement.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'search_pois' or 'search_by_tags', nor does it explain what makes this 'smart' search different or preferable. There's no context about prerequisites, limitations, or typical use cases beyond the generic mention of POI categories.

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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