list_countriesEvery country in the atlas with how many filming locations it holds, most first — answers "which country has the most filming locations". Countries with a browsable page carry its URL. Coverage reflects what Wikidata records, which is uneven and skewed to Europe and North America, so read these as records and not as an inventory of world film production.
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that coverage is uneven and skewed to Europe and North America, and warns that data reflects Wikidata records rather than a complete inventory. This is valuable behavioral context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose and sorting order, then adds the URL detail and data caveat. Every sentence earns its place with no waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and no output schema, the description covers the key aspects: what it returns (countries with counts and URLs), how it's sorted, and the data quality caveat. It's complete for a simple list tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the description doesn't need to explain parameters. The baseline for 0 params is 4, and the description appropriately focuses on output semantics instead.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists every country in the atlas with filming location counts, sorted most first, and explicitly answers the question 'which country has the most filming locations'. It distinguishes itself from siblings by focusing on country-level aggregation rather than location search or statistics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (to answer country-level questions about filming locations) and provides context about data coverage. It doesn't explicitly name alternatives, but the sibling list and the clear purpose make the usage context clear enough.
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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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.
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.
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.
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.