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filming-locations

by com.thefilmmap

Where a film, series or game was filmed

where_was_it_filmed

The main tool. Give a film or television title and get every place Wikidata records it as filmed at, with coordinates, plus the countries it records too coarsely to place. Covers 13,338 productions across 15,565 places. Two things to carry into any answer you write. First, video games AND anime are in here as well, and neither is filmed anywhere: their places are where they are SET (Wikidata P840, not P915), and every record says which through its relation field — never call one of those a filming location. Second, the gaps are real information: when countries_only is populated, Wikidata knows the production shot in those countries but not where, and the honest answer says so rather than guessing a street. This atlas never records which scene was shot where, so do not infer it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax places (default 50)
titleYesTitle, or its slug, e.g. "Skyfall", "game-of-thrones", "The Third Man"

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations, the description fully carries the behavioral disclosure burden and does so excellently: it explains that games and anime use set locations rather than filmed locations, that every record includes a `relation` field, that `countries_only` marks coarse data gaps, and that scene-level granularity is never available. This prevents the agent from making confident but false claims.

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 main purpose and then organizes critical caveats into clearly numbered 'First... Second...' sections. Every sentence earns its place, and the length is justified by the special cases an agent must understand before writing an answer.

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 that there is no output schema, the description provides enough of the return shape and interpretive rules—coordinates, countries_only, relation, coverage scale, and the absence of scene-level data—for an agent to call the tool and correctly use the results. Only sibling routing is implicit, which is adequately covered by other dimensions.

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?

The input schema already documents both parameters, title and limit, with 100% coverage, so the baseline is 3. The description gives example title forms and output caveats, but it does not add meaningfully new parameter-level semantics beyond what the schema already states.

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 core action and scope: give a film or television title and get every place Wikidata records it as filmed at, with coordinates and coarse countries. It is specific about the resource and output, but it does not explicitly name sibling tools or state what the tool is not, so it stops short of full sibling differentiation.

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 opens by calling itself 'The main tool' and clearly defines the input type and output, giving an agent solid context for when to use it. It does not however spell out when-not or explicitly route to alternatives such as search_productions for partial titles or what_was_filmed_here for reverse lookups.

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

A4.3/5.0
Disambiguation5/5

Each tool answers a distinct query type: aggregate statistics, country counts, nearby places, ranked places, name searches, production-to-places, and place-to-productions. The two full-question tools are clearly explicit inverses, so an agent should rarely select the wrong one.

Naming Consistency3/5

The set mixes multiple patterns: get_/list_/search_ verb prefixes, noun-based names like top_locations and locations_near, and full question phrases like what_was_filmed_here. Each name is descriptive, but there is no single consistent verb_noun convention across the surface.

Tool Count5/5

Eight tools is well-scoped for a read-only atlas: core lookup, inverse lookup, name search, geospatial search, ranking, country aggregates, and headline statistics. No tool feels redundant or missing at the same level of detail.

Completeness5/5

The domain is covered comprehensively: production-to-places, place-to-productions, location search, nearby search, ranking, country counts, and dataset-level statistics. For a Wikidata-backed read-only atlas there are no obvious dead ends; finer-grained scene data is explicitly out of scope.

Resources