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Geonames

by io.github.pipeworx-io

Search Geonames

search_geonames
Read-onlyIdempotent

Search for places (cities, towns, landmarks, regions) by name and get which STATE / PROVINCE / COUNTY / PREFECTURE / administrative division (German Bundesland, UK county, Canadian province, Japanese prefecture, Indian/Australian/Mexican state, etc.) they are in, plus country, coordinates, population, and feature type. Answers "what state is in", "which US/German/Australian state is in", "what province/county/prefecture/region is in" — the admin_region field is the state/province/county/prefecture (e.g. search_geonames("Naperville", "US") → Illinois; ("Heidelberg", "DE") → Baden-Württemberg; ("Leeds", "GB") → England; ("Osaka", "JP") → Osaka). Worldwide coverage. Example: search_geonames("Paris", "FR"). Use get_nearby to find places near a known location.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of results (default: 10, max: 100)
queryYesPlace name to search for (e.g., "Tokyo", "Grand Canyon")
_apiKeyYesGeoNames username
countryNoISO 3166-1 alpha-2 country code to filter (e.g., "US", "JP")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe search query string
totalYesTotal results count from API
placesYes
countryYesISO 3166-1 alpha-2 country code filter applied
returnedYesNumber of results in this response

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already indicate readOnly, openWorld, and idempotent hints. The description adds context about the admin_region field and worldwide coverage. It does not contradict annotations and provides useful behavioral details.

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 front-loaded with the primary purpose, includes clear examples, and ends with a sibling reference. Every sentence adds value, and the structure is logical.

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 complexity of the tool (search with multiple parameters and output schema), the description is comprehensive. It details the admin_region field, gives examples for various countries, and mentions output fields. It also references a sibling tool for nearby searches.

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% with descriptions for all 4 parameters. The description adds examples and explains the admin_region field's meaning, providing additional context beyond the schema.

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 explicitly states it searches for places by name and returns administrative divisions, country, coordinates, population, and feature type. It provides specific examples and distinguishes from the sibling tool get_nearby.

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

Usage Guidelines5/5

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 different countries and explicitly mentions when to use get_nearby as an alternative. It gives concrete instructions on how to use the tool.

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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TDQS

A3.6/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded; multiple polymarket_* scanners), and the mix of unrelated domains makes it hard to tell which tool is canonical for a task. The few geographic tools are distinct, but they are buried among dozens of non-geographic tools.

Naming Consistency2/5

Naming is a mix of verb_noun (search_geonames, resolve_entity), proper-noun prefixes (pipeworx_*, polymarket_*), and descriptive phrases (ask_pipeworx, bet_research, scan_competitor_ai_presence). No consistent pattern or verb style across the set.

Tool Count2/5

35 tools is far more than a Geonames-focused server needs, and most are unrelated to geospatial data. The count would be borderline for a general data platform, but it is excessive and unfocused for the stated server name.

Completeness1/5

The geographic surface is severely incomplete: only four tools (search_geonames, get_nearby, find_postal_codes, get_timezone) cover a tiny sliver of typical Geonames functionality like reverse geocoding, elevation, or distance calculations. The many non-geographic tools do not compensate for the missing core domain coverage.

Resources