Movie Scene Map

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile needs no restating. The one genuine addition is 'computed live', which tells the agent the figures are not cached and reflect current data. With no output schema, the description does describe the return shape (the enumerated figures), which is worth credit, but it says nothing about cost, response size, or shape of the aggregate values.

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?

A single front-loaded sentence that leads with the value proposition ('Headline figures computed live from the atlas') before the enumeration. The final clause about productions recorded only at country level is informative but slightly convoluted; still, every clause maps to a returned figure, so there is no filler.

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?

For a zero-parameter, no-output-schema aggregate tool, the description adequately discloses what comes back by listing each figure category. The main residual gap is that it does not indicate relative cost or whether the result is a single object keyed by metric, but that is minor given the simplicity of the 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 takes zero parameters, so per the baseline rule this scores 4. The description correctly implies a parameterless call by framing the result as fixed headline figures rather than something that can be filtered.

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?

States a specific resource (headline figures) and enumerates the aggregates returned: totals by medium, by kind of place, top countries, busiest/most famous locations, and unplaceable productions. 'Computed live from the atlas' signals it is an aggregate overview rather than a listing. It does not explicitly distinguish itself from sibling top_locations, which overlaps with the 'busiest and most famous locations' figures.

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?

Usage is only implied: the phrase 'headline figures' suggests an overview/orientation call, but there is no explicit 'use this when' statement, no exclusions, and no pointer to top_locations or search_locations for drill-down. An agent must infer the routing decision from the content rather than being told.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds real value beyond them — the descending sort order, the presence of a site URL per country, and an honest caveat that Wikidata counts are uneven and skewed to Europe/North America. It does not state whether the whole set is returned in one response or whether pagination applies.

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?

Three sentences, front-loaded with what the call returns and in what order, followed by the URL detail and the data-quality caveat. Every sentence carries content; no restatement of the name or filler.

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?

With no parameters and no output schema, the description carries the burden of describing the return shape, and it does: country name, count, optional site URL, ranked descending. The data-provenance caveat pre-empts a misinterpretation an agent might otherwise make about coverage.

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 takes zero parameters, so there is no per-parameter meaning to add and the baseline is 4. The description correctly implies a single unfiltered call rather than suggesting any filtering options exist.

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 states a specific verb and resource — 'lists every country in the atlas with its number of filming locations' — plus the sort order and the extra URL field, so an agent knows exactly what the call returns. It never names a sibling such as get_statistics or top_locations, so the boundary against those aggregate tools has to be inferred from the resource noun alone.

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?

Use is only implied: a complete, ranked country index is useful for browsing or for a country list to feed other calls, but the description never says when to prefer it over get_statistics or top_locations. There are no exclusions or prerequisites stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuinely new behavior: results are ordered 'most famous first', each carries `distance_km`, and the radius is capped at 500 km regardless of input. It does not discuss paging beyond the schema's limit, but that is minor.

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?

Two dense sentences, front-loaded with the core operation before the constraints, and no filler. The mid-sentence gloss 'what was filmed near a point' is slightly redundant with the opening clause, but the total length is well matched to the tool's simplicity.

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?

With no output schema, the description carries the burden of describing return values and does so by naming the ordering and the per-item `distance_km`. Combined with annotations covering the read-only profile and the schema covering optional filters, an agent has enough to call this correctly; only pagination behavior is unaddressed.

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?

Schema coverage is 60%, with latitude and longitude carrying no schema descriptions; the description compensates by specifying 'a latitude and a longitude in degrees' on a WGS84 coordinate system and warning that place names are not resolved. Radius defaults and bounds are restated from the schema, which adds little, and the category/limit parameters are left entirely to the schema.

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 opens with a specific verb and resource ('Lists the filming locations within a radius of a WGS84 coordinate') and adds the sort order and the `distance_km` field on each result, so the agent knows exactly what comes back. It differentiates itself only implicitly from siblings, via the caveat 'it does not look up place names', which points away from geocoding tools like search_locations without naming them.

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?

Usage is implied rather than stated: the clause 'what was filmed near a point' frames the scenario, and the radius default/cap tell the agent how to size a query. There is no explicit when-not guidance or named alternative among the many siblings (search_locations, what_was_filmed_here, where_was_it_filmed, top_locations), which is the main gap for a tool with this much sibling overlap.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely non-obvious behavior: results are ordered by fame rank, and that rank derives from the most widely covered production shot at the place rather than the place's own prominence — a ranking quirk an agent could not infer from structured fields.

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?

Two sentences, front-loaded with the core operation and filters, followed by the ordering caveat. No filler and nothing redundant with the parameter list.

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?

For a four-parameter search tool with a fully documented schema and rich annotations, this is nearly complete — the ranking behavior is explained and filters are covered. The remaining gap is that no output schema exists and the description never indicates what a result record contains or how the limit interacts with ranking, so an agent must discover that at call time.

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?

Schema coverage is 100% and all four parameters are documented in-schema, including the category key list and the country ISO-code option. The description restates the country filter (name or ISO code) and the notion of "kind of place" but adds no format or matching semantics beyond the schema, so the baseline 3 applies.

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 names a specific verb and resource ("Finds filming locations by name") plus the two supported filters, so an agent can distinguish it from siblings like search_productions or locations_near. It stops short of explicitly naming which sibling to use for reverse lookups or proximity queries.

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?

"By name" and the optional filters imply the usage context (the caller already has a place-name fragment), but there is no explicit when-to-use or when-not guidance and no named alternative for related tasks such as finding what was filmed at a place.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

The description provides critical behavioral context far beyond the provided annotations, which focus only on safety and idempotency. It explicitly details the fuzzy search logic (ignoring accents and case) and the semantic meaning of the results, particularly the `relation` field based on the production kind.

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 definition is extremely efficient, condensing all necessary behavioral constraints and functional scope into a single, coherent paragraph. No information is redundant, and the key features are well-structured.

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?

The description is exceptionally complete for a search tool. It covers input logic (fuzzy match, filtering), the result structure (kind, year, relation), and the specific scope of the database. The agent is fully equipped to use this tool correctly based on this definition alone.

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?

Although schema coverage is 100%, the description adds significant semantic value to the inputs. It clarifies that the `query` is a fuzzy match (case and accent insensitive) and explicitly lists the allowed media types for the `kind` parameter, guiding the agent on how to use these inputs effectively.

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 tool purpose is crystal clear: 'Finds productions by name.' It successfully distinguishes itself from sibling tools (like location searches) by focusing explicitly on media production entities (films, games, TV, etc.).

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 provides strong operational usage guidelines by detailing the search criteria (best match, Wikipedia coverage) and the existence of an optional filter (`kind`). It is slightly less than a 5 only because it does not explicitly state when to use it versus a generalized search tool (though the scope is clear).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world behavior, so the safety profile is covered. The description adds genuinely non-obvious semantics: fame rank derives from the single most widely covered production, so rank 1 is not the place with the most credits, and setting sort to productions changes the ordering to production count. That is real behavioral disclosure beyond the annotations.

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?

Two sentences, front-loaded with the core action and scope, followed by the ranking-definition sentence that carries the most decision-relevant information. No filler or restated title beyond the necessary framing.

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?

For a four-optional-parameter list tool with no output schema, the description covers scope, both sort modes, and the definition of the default ranking. Minor gaps remain: it does not indicate what a result entry contains or whether the list is paginated, though the limit parameter bounds size.

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?

Schema coverage is 100%, so the baseline is 3. The description still earns extra credit by defining what 'fame' actually means, which the schema only labels as 'Ranking (default fame)', and by clarifying that omitting country yields a worldwide ranking and that productions ordering produces a different (credit-count) ordering with concrete example cities.

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 opens with a specific verb and resource: 'Ranks the places in the atlas', then bounds the scope to worldwide, one country, or one category. This clearly separates it from search-style siblings like search_locations or locations_near, though it never names those siblings explicitly.

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?

Usage is implied rather than stated: the tool is for getting a ranked list of places, optionally scoped by country or category. The description explains what each sort mode produces but gives no explicit when-to-use/when-not guidance or pointer to an alternative tool such as search_locations when a ranked list is not what's needed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description rightly spends its words elsewhere: it discloses the result ordering ('most widely covered first') and warns that results include works merely set in a place (video games, anime, manga) flagged via the `relation` field. That is genuine behavioral context not present in structured fields.

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?

Three short sentences, front-loaded with what it returns and the ordering, followed by input format and the result caveat. No filler and no repetition of annotation data.

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?

With no output schema, the description usefully sketches the return shape by naming the `relation` field and its interpretation. What remains unstated is pagination/truncation behavior beyond the limit default and whether empty results are possible, but for a two-parameter read tool this is largely complete.

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?

Schema coverage is 100%, so both parameters are already documented, including the slug-preferred input and the default limit of 50. The description's restatement of slug-or-name adds no syntax or format detail beyond the schema, so baseline 3 applies.

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?

States a specific verb and resource: returns everything recorded as made at a place, ordered by widest coverage. The place-to-production direction is clear enough to distinguish it from the reverse-lookup sibling where_was_it_filmed, though that sibling is never named.

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 direction of lookup (place -> productions) is implied by the description, so an agent can infer this is the tool to use when starting from a location. There is no explicit when-to-use or when-not-to-use statement, and no mention of the alternative where_was_it_filmed or how the two relate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare read-only, idempotent and non-destructive, but the description goes well beyond them: coverage scale (37,259 productions / 37,350 places), the meaning of `relation`, the `countries_only` bucket for coarse records, and the `wiki_`-prefixed fields sourced only from the production's own article. The closing caveat that it records a filming place but not which scene was shot there is exactly the kind of expectation-setting an agent needs.

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?

It is front-loaded with the return value and every sentence contributes new information about outputs or data limits. It is a dense single block without structure, but there is no redundant or filler wording to cut.

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?

There is no output schema, so the description carries the full burden of explaining return shape, and it does so: coordinates, countries, relation, countries_only, and wiki_ fields. For a two-parameter lookup tool, nothing an agent needs in order to call and interpret it is missing.

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?

Schema description coverage is 100% and both parameters (title with slug examples, limit with default 50 and max 200) are already documented in the schema. The description adds no further meaning about parameter behavior or format, so the baseline of 3 applies.

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?

States a specific verb and resource: 'Returns every place recorded for a film, series, game, anime or manga, with coordinates.' It also disambiguates the core semantic question (filmed-at vs. set-in via the `relation` field), so an agent knows exactly what class of answer to expect.

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 applicability is strongly implied by the filmed-vs-set distinction, which tells the agent this tool answers 'where did production X happen.' However, it never names or excludes a sibling such as what_was_filmed_here (reverse lookup) or search_productions (title discovery), so the routing decision is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.