get_statisticsHeadline statistics computed live from the atlas: totals by type, top countries, busiest founding century, oldest landmarks, geographic extremes and the most famous entry. The source for claims like "which country has the most castles" or "when were castles built"; the full write-up lives at thecastlemap.com/statistics/.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: geospatial search (castles_near), single-record retrieval (get_castle), aggregate statistics (get_statistics), country overviews (list_countries), random discovery (random_castle), name-based search (search_castles), and fame-based rankings (top_castles). The only slight overlap between list_countries and get_statistics is minimal and both descriptions clearly separate them.
All tool names use lowercase snake_case and are self-explanatory, but they mix verb-first patterns (get_, list_, search_) with adjective or noun-first patterns (random_castle, top_castles, castles_near). This is a minor deviation from a fully consistent verb_noun convention, though the inconsistency does not hinder readability.
With 7 tools, the set is well-scoped for a castle atlas. Each tool covers a distinct need—search, get, near, top, random, stats, countries—without redundancy or bloat.
The toolset covers most read-oriented workflows: finding, retrieving, ranking, and statistics. A notable gap is the lack of a way to list all castles in a country or category without a name search term; search_castles requires a name substring and top_castles returns only the most famous. This is a workaround by using search with a broad term, but it's not a first-class operation.