aloha.fyi Hawaii

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful context about the curated dataset (450+ spots) and geographic scope, but does not disclose return format, ordering, or potential limitations.

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 two sentences, with the first sentence delivering the core purpose and the second offering practical example queries. It is concise, front-loaded, and contains no filler or redundant information.

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 and simple optional parameters, the description provides enough context for an AI agent to select and invoke the tool correctly. It covers scope, examples, and usage triggers, though it does not describe the result format; this is acceptable for a straightforward discovery 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 input schema has 100% description coverage for all four parameters, so the schema already documents each parameter. The description adds example query values and category examples, but these are illustrative rather than essential, keeping it at the baseline for schema-heavy coverage.

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 specifies the tool's function: finding restaurants, coffee shops, poke bars, ramen, bakeries, and food trucks in Waikiki and across Oahu. It distinguishes itself from sibling tools by focusing on dining/food, whereas siblings cover deals, weather, itinerary planning, events, and tours.

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 provides example user queries that should trigger this tool ('where should I eat in Waikiki', 'best poke on Oahu'), giving clear usage context. It does not explicitly state when not to use it or name alternatives, but the examples make the intended use evident.

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?

Given the annotations (readOnlyHint=true, destructiveHint=false, idempotentHint=true), the description adds behavioral context by revealing it returns low-price options sorted by price and derives from Groupon. This goes beyond the annotations, which already signal a safe, read-only operation. No contradictions with 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?

The description is two concise sentences with no filler. The first sentence states the main purpose, and the second adds key behavioral details (return content, sorting, and usage context). Every word earns its place.

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 read-only deal-listing tool, the description covers the essential elements: purpose, usage context, return content, and sorting behavior. The schema covers parameters, and no output schema is expected. It is sufficiently complete for an AI agent to select and invoke 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 provides full descriptions for all three parameters (limit, activity, max_price_dollars), and the coverage is 100%. The description does not add parameter-specific semantics beyond the schema; it only reinforces the general 'budget' theme. Thus, the baseline of 3 is appropriate.

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 'find[s] budget deals and discounts for Hawaii activities' with a specific verb and resource. It also specifies the return type ('Groupon deals and low-price options') and ordering ('sorted cheapest first'), which distinguishes it from sibling tools like search_hawaii_tours or find_hawaii_restaurants.

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 an explicit usage trigger: 'Use when users want affordable Hawaii experiences or budget travel tips.' This gives clear context for when to invoke the tool, though it does not mention explicit alternatives or exclusions. Still, it is more than just implied usage.

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=true and destructiveHint=false, so the description adds value by disclosing return data: temperature, precipitation, wind speed, UV index, and a 3-day forecast. It does not contradict annotations. However, the phrase 'any Hawaiian island' is slightly overbroad given the island enum limits to four specific islands, though this is a minor limitation and not a behavioral 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?

The description is concise at two sentences. It front-loads the core purpose in the first sentence, and the second sentence provides usage triggers and return fields. There is no redundant text; every sentence earns its place.

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?

Despite having no output schema, the description explains what is returned (temperature, precipitation, wind speed, UV index, 3-day forecast) and gives concrete usage cases. It does not mention units or island restrictions, but the schema provides those constraints. For a simple weather tool, this is sufficiently 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?

The input schema has 100% coverage with descriptions for both 'island' and 'days'. The description does not add additional parameter-level meaning beyond examples like 'Maui' and 'North Shore', but these are not necessary since the schema already explains the parameters. Baseline of 3 is appropriate given high schema coverage.

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 'Current weather, forecast, and surf/wind conditions for any Hawaiian island,' which specifies the main function with a verb and resource. It distinguishes this tool from siblings like restaurants, deals, events, and tours, leaving no ambiguity about its purpose.

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 gives usage examples ('what's the weather in Maui this week' or 'is it good surf conditions on the North Shore today'), clearly indicating when to use this tool. It does not mention alternatives or exclusions, but the sibling tools cover different domains, making it clear the weather tool is the right choice for weather/surf queries.

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=true and destructiveHint=false. The description adds that results are picked from a 'live catalog,' implying dynamic selection and possibly non-deterministic output, which aligns with idempotentHint=false. It also discloses the return structure, giving useful context beyond the structured attributes.

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 two sentences, front-loaded with the action and result, and then gives usage examples. Every word earns its place—no fluff 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 the simple parameter set (all optional, fully described) and no output schema, the description covers what the tool returns (structured itinerary components) and when to use it. It is complete for the tool's complexity level.

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%, with each parameter (vibe, island, max_budget_per_person) having a clear description. The tool description does not add extra parameter-specific guidance, but the schema fully documents them, 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 clearly states the tool builds a same-day or trip itinerary for a Hawaiian island, listing specific output components (morning activity, lunch spot, etc.). This distinguishes it from siblings that focus on individual services like restaurants, deals, weather, events, or tours.

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 concrete example queries that trigger this tool ('plan my day in Oahu', 'what should I do Saturday in Maui', 'family itinerary for Kauai'), making the intended use obvious. It doesn't explicitly name alternatives or exclusions, but the examples effectively differentiate when to use it versus siblings.

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=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds 'refreshed weekly from venue and promoter calendars', providing context about data freshness and source. No contradiction with annotations, but no additional behavioral quirks are disclosed.

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?

Concise two-sentence description. The first sentence states the function and data source, the second gives usage context. Every word earns its place, with no redundant repetition of schema or annotation 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?

The tool has no output schema, so the description should help the agent understand what to expect. It says 'Find upcoming events' but doesn't explain return structure or result count. The 'refreshed weekly' clue implies potential staleness but lacks specifics. Overall, adequate for a simple search tool but missing some practical details.

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 covers 67% of parameters with descriptions (query and days_ahead). The island parameter lacks a description, relying on enum values. The tool description does not compensate for this gap. Since coverage is moderate, and enums are self-explanatory, the baseline applies, and the description adds minimal parameter meaning 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 uses a specific verb 'Find' with a clear resource: 'upcoming events, concerts, festivals, and nightlife across the Hawaiian islands.' This distinguishes it from sibling tools like find_hawaii_restaurants or search_hawaii_tours, which target different domains.

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 states when to use: 'Use when users ask what's happening in Hawaii or want entertainment options.' This gives clear context, though it doesn't explicitly name alternatives or exclusions. It still provides sufficient guidance for an agent to select this tool over siblings.

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=true and destructiveHint=false, so the safety profile is covered. The description adds that it returns tours from specific providers (Viator, GetYourGuide, Klook, Groupon) with affiliate links, which is useful context but lacks deeper behavioral details like pagination or result ordering.

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 with no wasted words. The first sentence states purpose and scope, the second adds source details, and the third gives usage guidance. Every sentence earns its place.

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 search tool with full schema coverage and clear annotations, the description is sufficient. It hints at return content (provider tours with booking links) but doesn't specify the response structure, which is acceptable given no output schema and the simplicity of a search result.

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%, so the schema fully documents all parameters. The description only restates the categories (keyword, island, price range) that map to existing schema fields, adding no new semantic value beyond the baseline.

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 ('Search') with a clear resource ('1,500+ bookable Hawaii tours and activities') and scoping dimensions ('by keyword, island, price range'). It clearly distinguishes from sibling tools like find_hawaii_restaurants and search_hawaii_events.

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 states when to use the tool: 'Use this when users ask about Hawaii tours, activities, or things to do.' However, it doesn't mention alternatives or when not to use it, so it stops short of full guidance.

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