get_platform_infoReturns Tuki positioning, verticals, contact, and key URLs. Use to answer "what is Tuki", "how does Tuki work", "is Tuki trustworthy".
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so safety is known. The description adds informative context about the returned data categories (positioning, verticals, contact, URLs), going beyond annotations. No contradiction.
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: the first states the output contents, the second gives explicit usage examples. Every word earns its place, and the most important information is front-loaded.
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, parameterless, read-only informational tool with strong annotations and clear usage scenarios, the description is complete. No output schema is needed because the description clearly enumerates the types of information returned.
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 schema coverage is trivially 100%. The baseline for zero parameters is 4; the description provides all necessary context by explaining what information 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 states a specific action ('Returns') and enumerates the exact resources (positioning, verticals, contact, key URLs). This clearly distinguishes it from sibling tools that focus on travel-specific items like accommodations or destinations.
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 provides use cases ('what is Tuki', 'how does Tuki work', 'is Tuki trustworthy'). It does not explicitly mention alternatives, but the sibling context makes it obvious that this is the general platform info tool rather than a specific content detail tool.
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.
Every tool targets a distinct resource or action: get_* tools retrieve details for specific entity types, search_* tools query specific verticals, and list_* tools enumerate categories. The potential overlap between search_accommodations and search_hotels is explicitly disambiguated in descriptions, and search_unified vs per-vertical searches have clear routing rules.
All tools follow a consistent verb_noun pattern: get_*_detail for lookups, search_* for queries, list_* for enumerations, and recommend as the sole one-word but still predictable exception. Naming is uniform with snake_case throughout, making the overall structure highly predictable.
With 23 tools, the server is on the heavier side, but the breadth of verticals (accommodations, cars, events, experiences, hotels, destinations, bus routes, travel guides, solutions) justifies each tool's presence. The number is slightly above the ideal but still well-scoped for a multi-category marketplace.
The tool surface covers the full browsing and recommendation lifecycle: search and list across verticals, retrieve detailed information for any entity, access editorial travel guides, and generate checkout URLs for booking. No critical operations are missing for the server's purpose as a read-only recommendation and conversion layer.