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BACH-AI-Tools

Geodb Cities MCP Server

places_near_place

Find nearby cities, islands, or administrative areas within a specified radius from a given location, with filters for population, country, time zone, and name.

Instructions

Get places near the given place, filtering by optional criteria.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typesNoOnly places for these types (comma-delimited): ADM2 | CITY | ISLAND
radiusYesThe location radius within which to find places0
distanceUnitNoThe unit of distance to use: MI | KM
countryIdsNoOnly places in these countries (comma-delimited country codes or WikiData ids)
excludedCountryIdsNoOnly places NOT in these countries (comma-delimited country codes or WikiData ids)
timeZoneIdsNoOnly places in these time-zones
minPopulationNoOnly places having at least this population0
maxPopulationNoOnly places having no more than this population0
namePrefixNoOnly places whose names start with this prefix. If languageCode is set, the prefix will be matched on the name as it appears in that language.
namePrefixDefaultLangResultsNoExample value:
languageCodeNoDisplay results in this language
asciiModeNoExample value:
hateoasModeNoExample value:
includeDeletedNoWhether to include any places marked deleted: ALL | SINCE_YESTERDAY | SINCE_LAST_WEEK | NONE
offsetNoThe zero-ary offset into the results0
sortNoHow to sort the results. Format: ±SORT_FIELD,±SORT_FIELD where SORT_FIELD = countryCode | elevation | name | population
placeIdYesExample value:
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 only mentions the core action and optional filtering, lacking details on permissions, rate limits, pagination (despite an 'offset' parameter), error handling, or what the output looks like (no output schema). For a tool with 17 parameters, 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, clear sentence that efficiently states the core action and scope. It's front-loaded with the main purpose and avoids unnecessary words, though it could be more structured by explicitly mentioning key parameters or output format.

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 complexity (17 parameters, no annotations, no output schema), the description is insufficient. It doesn't explain the return type, pagination behavior, error cases, or how 'places' are defined relative to siblings. For a rich filtering tool, more context on usage and output is needed to be complete.

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 fully documents all 17 parameters. The description adds no parameter-specific information beyond implying filtering exists ('optional criteria'), which doesn't enhance understanding of individual parameters. This meets the baseline for high schema coverage but doesn't add value.

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

Purpose3/5

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

The description states the purpose ('Get places near the given place') with a verb and resource, but it's vague about what 'places' means compared to siblings like 'admin_divisions_near_division' or 'cities_near_division'. It doesn't specify if 'places' refers to cities, administrative divisions, or other geographic entities, making sibling differentiation unclear.

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 like 'places_near_location' (which uses coordinates instead of placeId) or 'admin_divisions_near_division'. It mentions 'filtering by optional criteria' but doesn't explain when those filters are appropriate or what scenarios this tool is designed for.

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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