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Glama

InfraNode

by dev.infranode

City Data by Type

get_city_resource
Read-onlyIdempotent

Fetch ANY per-city data type by its key (generic accessor, 81 data types).

One tool for the whole breadth of InfraNode: live data (air, traffic, transit stops, parking, charging, water-level, flood, sharing, fuel-prices, webcams, station-departures/-arrivals/stations, ...), statistics (demographics, unemployment, tourism, accidents, crime-stats, indicators, land-values, tax-rates, insolvencies, ...), multi-year TIME SERIES (sustainability: SDG indicators per municipality, one value per year from 2006 to 2023, so trends can be answered without stitching snapshots), infrastructure and environment (solar, solar-roofs, district-heating, energy, heritage, tree-cadastre, playgrounds, public-toilets, markets, education, ...) and more. Discover the valid keys and per-city coverage with get_city_overview(slug) or the infranode://catalog resource; the resource enum lists every key. Uncovered types return source_status="not_covered" (plus where they ARE available), never an error. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesCity identifier, e.g. 'berlin' or 'hamburg'. Resolved leniently: the German name with or without umlauts, any casing, a common English exonym or short form also works (München/munich/munchen -> muenchen, cologne -> koeln, frankfurt -> frankfurt-am-main). An unknown name returns 404 with a 'Meintest du ...?' suggestion. list_cities gives the canonical slugs.
resourceYesData type key to fetch, exactly as listed by get_city_overview / the infranode://catalog resource (the 'type' field), e.g. 'charging', 'parking', 'demographics', 'solar', 'district-heating'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
metaYes

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds important behavior: uncovered types return source_status='not_covered' (never an error) and location hints. This goes beyond annotations and enhances the agent's understanding of the tool's safe, non-failing nature.

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 front-loaded with the core purpose in the first sentence. It then provides a comprehensive but verbose list of example data types. While the list demonstrates breadth, it could be more concise. Overall, it is well-structured and informative.

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 tool's complexity (81 data types, 2 params, output schema exists), the description adequately covers the generic accessor role, error handling, and discovery methods. The output schema presumably covers return format, so its absence in the description is acceptable. The description is complete enough for an agent to understand when to use the tool.

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 coverage is 100%, with both slug and resource already described in detail (slug's lenient resolution, resource's enum). The description does not add new semantics for the parameters but reinforces the tool's role. Baseline 3 is appropriate since the schema handles the parameter documentation.

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 'Fetch ANY per-city data type by its key (generic accessor, 81 data types)', providing a specific verb, resource, and scope. It distinguishes itself from sibling tools like air_quality or station_board_arrivals which are specialized for individual data types.

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 advises discovering valid keys via get_city_overview or the catalog resource, and explains that uncovered types return a 'not_covered' status. This gives the agent context on when to use this tool versus overview tools. However, it does not explicitly contrast with specialized siblings.

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

A4.1/5.0
Disambiguation3/5

Most tools have distinct purposes, but there is potential confusion between 'get_city_resource' and specific resource accessors like 'weather', 'air_quality', 'transit_departures', 'station_board_arrivals', and 'station_board_departures'. The descriptions do clarify that some specific tools exist for convenience or source-specific details, but the boundary isn't always sharp. Also, 'compare' could overlap with using 'get_city_resource' repeatedly. An agent might hesitate between using the generic resource accessor and the named tool.

Naming Consistency4/5

The naming convention is mostly consistent: verbs like 'get', 'list', 'compare', and 'pois' (abbreviation) are used. The pattern is generally 'verb_noun' (e.g., 'get_city', 'list_cities', 'station_board_arrivals'). Minor deviations include 'pois' being an acronym rather than a full verb phrase, and 'air_quality' vs 'weather' implying a noun rather than an action. But overall it's predictable and readable.

Tool Count5/5

12 tools is a well-scoped count for a city data platform. The function set covers discovery (list_cities, sources), overview (get_city_overview), base data (get_city), specific data types (weather, air_quality, transit_departures, station_board_*, pois), a generic accessor (get_city_resource), and a comparison tool (compare). Each tool feels necessary and the set is not overwhelming.

Completeness4/5

The tool surface is quite comprehensive for a read-only city information server. It provides discovery (list_cities, get_city_overview), base data, and access to 81 data types via get_city_resource. The named tools cover the most common queries (weather, air quality, transit). A minor gap is the lack of a tool to aggregate or search across cities (though 'compare' helps). Editing or write operations are not expected here, but for read-only, it's nearly complete.

Resources