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?

Annotations already establish readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds useful behavioral context beyond those, noting that results are ordered cheapest first and that well-reviewed Viator options are preferred at similar prices.

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: the first states the core function, the second adds ordering and preference behavior, and the third gives the user-intent trigger. 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?

For a simple read-only search tool with a 100% documented schema, the description covers the essential behavior and use case. There is no output schema, so a more explicit note about return format would be nice, but the sorting and selection behavior already communicated make the definition practical.

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 parameters are already well documented. The description adds the 'price cap' concept, which maps to max_price_dollars, and the 'budget-friendly' framing, but it does not need to add much because the schema carries the parameter meaning.

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 ('budget-friendly Hawaii tours and activities under a price cap'). It distinguishes itself from related siblings like search_hawaii_tours by emphasizing cost filtering and deal-oriented ordering, so an agent can tell them apart.

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 'Use when users want affordable Hawaii experiences or budget travel tips,' giving a clear trigger condition. It does not name sibling tools or state when not to use it, but the when-to-use direction is strong enough for 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?

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, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds meaningful behavioral context beyond annotations: the inventory size, the four booking platforms aggregated, the existence of booking links in results, and the ability to filter by source. This sets accurate expectations for what the tool returns.

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 with no filler: the first fronts the action and value proposition, the second explains return contents and when to use it. Every clause earns its place, and it avoids restating the tool name or title.

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 read-only search tool with rich annotations and 100% schema coverage, the description is nearly complete. It covers what is searched, what is returned, and when to use it, and the schema handles parameter constraints. A fully ideal description might enumerate result fields, but none are critical for correct invocation.

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 by mapping source to concrete platforms (Viator, GetYourGuide, Klook, Groupon) and grouping query, island, and max_price_dollars into meaningful search dimensions. Limit is not mentioned in the description, but the schema fully documents it.

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 concrete resource ('2,400+ bookable Hawaii tours and activities') and lists filtering dimensions (keyword, island, price range). It clearly differentiates from sibling tools like find_hawaii_restaurants or search_hawaii_events by focusing on bookable tours and naming aggregator sources.

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 final sentence explicitly states when to use the tool: 'when users ask about Hawaii tours, activities, or things to do.' It does not explicitly list exclusions or alternatives, but the positive usage context is clear enough for an agent to route requests appropriately.

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