list_countriesEvery country in the atlas with its landmark count, most first — answers "which country has the most castles" (Spain leads). Returns country name and ISO code per row; country pages are browsable from the countries_index URL.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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.
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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.