castles

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

Without annotations, the description discloses key behaviors: results are sorted by distance, include 'distance_km', and the radius defaults/max are specified. It doesn't mention idempotency or side effects, but the listing nature implies read-only operation.

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 concise sentences with essential information front-loaded. No filler or redundancy.

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 no output schema, the description adequately describes the output format (distance_km, sorted). It mentions the default/max radius and provides usage guidance. Minor omission: no mention of the 'limit' parameter's default behavior.

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 40% (limit and radius_km have descriptions; latitude, longitude, category do not). The description adds radius defaults but does not clarify the missing parameters. It provides marginal value beyond 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 specifies the verb 'List' and the resource 'landmarks within a radius of a WGS84 coordinate', and clarifies the ordering ('nearest first'). It provides a concrete usage example ('For "castles near <place>"...'), which distinguishes the tool from siblings like 'search_castles' that likely use text-based 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?

The description gives explicit instructions for the common use case ('geocode the place yourself, then call this'), which aids selection. While it doesn't explicitly state when not to use this tool, the guidance is clear and actionable.

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?

No annotations are present, so the description carries the full burden. It clearly implies a read-only 'Fetch' operation and discloses the full set of return data, including licensing and readership signals. However, it does not mention error handling, not-found behavior, or rate limits, which prevents a perfect score.

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 a single dense paragraph with every clause adding value: it specifies the resource, input format, return fields, and usage guidance. No filler or redundant text is present.

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 simple getter with one parameter and no output schema, the description covers the input requirements, return value contents, and fallback to search_castles. It omits error cases or what happens if no match is found, but these are minor gaps for a fetch-by-identifier 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 schema only says 'Slug (preferred, e.g. "himeji-castle") or exact name', but the description enriches this by showing the exact example 'palace-of-versailles', emphasizing the preferred format, and adding the fallback advice. This goes well beyond the schema's generic parameter description.

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 uses a specific verb ('Fetch') and resource ('one landmark's full record'), and lists the specific fields returned (coordinates, founding year, fame rank, photo, Wikipedia link, readership signals). It also distinguishes itself from search_castles by specifying that it takes a slug or exact name, making the tool's scope clear.

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 explicitly says 'Unsure of the slug? Call search_castles first', providing a clear alternative path. It also states the preferred input format (slug) vs exact name, giving direct guidance on when to use this tool versus searching.

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?

No annotations provided, so description carries full burden. It says 'computed live from the atlas' indicating real-time computation. It lists what statistics are included but doesn't specify performance or whether it's read-only. Still, it gives adequate behavioral context for a stateless read operation.

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 that are front-loaded with the main purpose and include specific examples. No wasted words.

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 no output schema, the description lists the categories of statistics (totals, top countries, etc.) and references a full write-up URL. It could detail the response format more, but for a simple stats tool it's fairly 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?

There are no parameters, so the description provides all necessary semantic meaning by detailing what statistics the tool returns.

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 provides headline statistics computed live from the atlas, listing specific categories like totals by type, top countries, etc. It distinguishes itself from sibling tools by focusing on aggregate data rather than individual castles or searches.

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 explicitly says it's 'the source for claims like which country has the most castles', giving clear usage context. It does not explicitly state when not to use, but the alternative tools (get_castle, top_castles) are implied.

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?

With no annotations, the description carries full burden for behavioral transparency. It discloses that results are ordered most first, each row contains country name and ISO code, and country pages are accessible via the countries_index URL. This gives useful behavioral context beyond a bare 'list countries' statement, though it does not cover pagination or data freshness.

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 a single sentence that front-loads the core action and result, then efficiently adds ordering, the example answer (Spain), and output details. Every clause earns its place, with no wasted words or redundant schema repetition.

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 tool with no output schema, the description is complete: it explains what is returned (country name and ISO code), how it is ordered (most first), what question it answers (most castles), and how to navigate further (countries_index URL). No significant gaps remain for an agent to invoke this tool correctly.

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 input schema has zero parameters, so the baseline is 4. The description adds no parameter-level detail because none exists, and the no-parameter nature is consistent with a tool that simply returns all countries. No additional semantic guidance is needed.

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 its landmark count, sorted most first, and explicitly answers the question 'which country has the most castles' (Spain leads). This distinguishes it from sibling tools like get_castle or search_castles, which focus on individual castles or searches.

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 clear context for when to use this tool: when you need a complete country-level overview with counts, especially to identify which country has the most castles. It does not explicitly mention alternatives or exclusion criteria, but the purpose is unambiguous enough to guide selection.

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?

With no annotations, description discloses key behaviors: returns one random record, optional country filter. Adequate for a simple read tool.

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?

Single sentence front-loads purpose and is perfectly concise with 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?

Given the tool's simplicity (one optional param, no output schema), the description covers return type, optionality, and intended use completely.

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 parameter description already explains 'country' as optional. Tool description adds context ('optionally limited to a country') but minimal extra value.

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 it returns one random landmark with full record, optionally filtered by country. It distinguishes from siblings like get_castle (specific) and castles_near (proximity).

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?

Explicitly mentions use cases like discovery, quizzes, and 'castle of the day'. Implies when not to use via sibling tool names but lacks explicit exclusions or alternatives.

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?

No annotations exist, so the description carries full burden — and it delivers: case/accent insensitivity, substring semantics, best-match-first ordering, and result contents including coordinates, founding century, fame rank, and links. It also discloses failure behavior with retry advice.

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, each earning its place: matching semantics, result ordering/content, and failure handling. Information is front-loaded with the core search behavior before the optional filters and result details.

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 appropriately explains what results contain and how they are ordered. With 100% parameter schema coverage, optional filters, and clear failure guidance, everything an agent needs to call the tool correctly is present.

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 adds value beyond the schema by specifying accent/case-insensitive substring matching and the country name-or-ISO-code flexibility, and by summarizing the filtering intent. It slightly improves but does not heavily extend the schema's parameters.

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 ('search'), a precise resource ('the atlas’s 7,738 castles, fortresses, palaces and ruins'), and the matching behavior ('by name'). It is clearly distinguishable from siblings like castles_near and random_castle, which target different retrieval modes.

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?

Provides clear usage context: substring search by name, optional country/category filters, and a retry strategy when nothing matches. It does not explicitly name sibling alternatives or state when not to use it, but the behavioral guidance is strong and actionable.

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?

No annotations are provided, so the description carries the burden. It explains the ordering mechanism (Castlemap fame rank, blend of Wikipedia coverage and readership) and gives a concrete example (Palace of Versailles as rank 1), adding useful behavior beyond schema. It does not address read-only nature or output format, but for a list tool this is adequate.

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 purpose and ranking logic. No wasted words; every clause adds value.

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 three optional parameters, no output schema, and no annotations, the description covers the core functionality, ordering, filters, and an example. It is sufficiently complete for a simple top-list tool, though it could mention default limit or handling of invalid countries.

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 covers limit and country with descriptions, and category has enum values but no description. The description adds 'filter by country and/or category' but does not elaborate on parameter meanings or values. With 67% schema coverage, the description provides moderate additional value but does not fully compensate for the undocumented category semantics.

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?

Description clearly states the tool lists the most famous landmarks worldwide or in a country, ordered by a specific fame rank. It distinguishes itself from siblings by explicitly addressing 'most famous castles in <country>' and mentioning filters.

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?

Provides clear usage context: 'direct answer to most famous castles in <country>' and indicates filtering by country and/or category. Does not explicitly mention when not to use or name alternatives, but the intended use case is well implied.

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