Ask Hawaiʻi

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

No annotations are provided, so the description carries the full burden. It usefully discloses the upstream source (NWS) and that only currently active alerts are returned, but says nothing about update frequency, severity/urgency fields, empty-result behavior, or whether marine and offshore zones are included.

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?

A single well-formed sentence with the scope front-loaded and the optional filter trailing. Nothing is wasted and nothing is buried.

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 tool with one optional parameter and no output schema, the description is nearly sufficient. The only meaningful gap is the missing boundary against the sibling weather tool, which an agent would benefit from given five Hawaii-related siblings.

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% and the single island parameter already enumerates the valid values in the schema. The description's 'optionally filtered by island' merely restates the optionality, adding no new semantics 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?

States a specific resource (active National Weather Service alerts in Hawaiʻi) and enumerates concrete alert types (surf, flood, wind, tsunami), so the agent knows exactly what data comes back. It does not explicitly distinguish itself from the sibling get_hawaii_weather, leaving ambiguity about whether forecasts and alerts overlap.

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?

Usage is implied by the word 'Active' — this is the tool for current hazard notifications rather than general conditions. However, it never states when to prefer it over get_hawaii_weather or get_hawaii_headlines, and offers no exclusions or prerequisites.

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?

With no annotations, the description carries the burden but does give useful return-shape context: it returns every detail line and source links, which tells the agent to expect a larger payload than a search hit. It says nothing about error behavior for invalid/expired ids or whether ids are stable, which matters for a detail-lookup tool.

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?

One sentence, front-loaded with the action and resource, with the id provenance and the return contents appended in order of usefulness. Nothing is wasted and nothing needs reordering.

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 one-parameter, non-destructive detail fetch with no output schema, the description covers what it does, where the id comes from, and what comes back. Only the invalid-id behavior is left unaddressed, which is a minor gap at this 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 0% and the only parameter is a bare string, so the description's note that the id comes from search_hawaii results is the sole semantic anchor and does add real value. However, it gives no format hints, no statement that the id is opaque or case-sensitive, and no failure semantics.

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?

States a specific verb and resource ("Get the full details of one Ask Hawaiʻi entry") plus the lookup key ("by its id"), which cleanly separates it from the search/list siblings. An agent can tell this is a single-record detail fetch without opening the schema.

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?

"id (from search_hawaii results)" gives concrete guidance on how to obtain the required input, effectively routing the agent through search_hawaii first. It stops short of explicit exclusions (e.g., what to do when the id is unknown or stale), so usage is clear but not fully bounded.

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?

With no annotations, the description does real work: it discloses that results are limited to titles and links (not full articles), that only three named outlets are covered, and that freshness is capped by a 7 a.m./7 p.m. Hawaiʻi-time refresh cycle — so an agent knows it cannot retrieve older or full-text news here. It stops short of any failure-mode or rate-limit context.

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 short sentences with zero waste. Content and sources are front-loaded, with the cadence detail placed second as supporting context.

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 annotations and no output schema, the description supplies everything needed: what comes back (titles and links), from where, and how fresh it is. Nothing required to call it correctly is missing.

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 tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. The description correctly does not invent filtering options such as topic or source selection, matching the empty 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?

States a specific resource (today's Hawaiʻi news headlines, titles and links) and names the three exact sources: Hawaii News Now, KHON2 and Civil Beat. An agent can immediately tell this apart from get_hawaii_alerts, get_hawaii_weather and search_hawaii without inspecting any schema.

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 word 'Today's' plus the twice-daily update cadence implies the use case (current headlines), but the description never states when to prefer this over search_hawaii for older stories or list_hawaii_topics. Usage is implied rather than guided, and no alternatives are named.

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?

With no annotations, the description carries the full behavioral burden. It usefully discloses the data source (NWS) and that the forecast is live, which implies a read-only lookup, but it does not cover return behavior, error handling, or any rate/auth constraints.

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 front-loaded sentence with no wasted wording. The examples are useful and earned, and the core purpose is stated immediately.

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 one-parameter read tool, the description states the purpose, source, and valid place examples. Because there is no output schema and no annotations, there is a minor gap around the exact forecast return format, but the core information needed to call it is present.

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 0%, so the description must compensate. It does so by defining the parameter domain as a Hawaiʻi place and supplying several concrete examples, though it does not specify exact input formatting beyond those examples.

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 resource and action: a live weather forecast from the U.S. National Weather Service for a Hawaiʻi place. It is clear what the tool returns and gives concrete place examples, though it does not explicitly name sibling tools such as get_hawaii_alerts or get_hawaii_headlines to disambiguate.

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 gives no explicit when-to-use or when-not-to-use guidance. It also does not mention alternatives, so the agent must infer that this is for forecasts rather than alerts, headlines, or other Hawaiʻi information.

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?

No annotations exist, so the description carries the full behavioral burden; it does disclose the shape of what comes back (categorized topics with ids), which implies a safe read-only enumeration. It does not state whether the list is static or paginated, or whether any auth/quota applies, leaving genuine gaps for an unannotated tool.

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?

A single front-loaded sentence with no filler; the scope, grouping, and included identifiers all appear before any trailing clauses. Nothing could be removed without losing signal.

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 listing tool with no annotations and no output schema, the description supplies the essential return shape and scope. Only minor context is missing, such as list size or whether results are stable, which keeps it from a 5.

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 tool takes zero parameters, so the baseline is 4 and there is nothing for the description to disambiguate. It adds no misleading parameter language either.

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?

States a specific verb and resource ('List every topic Ask Hawaiʻi covers') and adds the return structure ('grouped by category, with ids'). It is unambiguously the only enumeration tool among siblings that all fetch or search specific content, so an agent cannot confuse it with get_hawaii_entry or search_hawaii.

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 phrase 'with ids' hints that this is a discovery step whose output feeds other calls, but the description never says when to reach for it over search_hawaii or names any prerequisite. Usage is inferable rather than stated.

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?

With no annotations, the description carries full burden, and it usefully discloses that results carry 'official sources and a last-checked date' — behavior an agent could not get from the schema. It still omits result ordering, whether curated content can go stale, and any rate or scope limits.

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: scope first, output guarantee second, and concrete query examples last for pattern-matching. Zero filler and properly 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 4-parameter read-only search with no output schema and no annotations, the description covers purpose, coverage breadth, and result provenance (official sources, last-checked date). Minor gaps: no guidance on the limit cap or on empty-result behavior.

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 description adds nothing about the four parameters — no mention of island, type, or limit usage, and no guidance on writing effective queries is needed since the schema already says 'in plain words.' At 75% schema description coverage the schema does the heavy lifting, so baseline 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?

A well-defined verb-plus-resource scope: 'Search verified Hawaiʻi visitor and resident facts,' with concrete domains (beaches, ocean safety, wildlife rules, sunscreen laws, lodging taxes) that differentiate it from the narrow getters in its sibling set. However, it never explicitly disambiguates against get_hawaii_weather or get_hawaii_alerts, which overlap its 'ocean safety'/'safety' coverage.

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 two example questions ('Do I need a reservation for Hanauma Bay?' / 'How close can I get to a sea turtle?') make the retrieval context concrete and easy to match. There are no exclusions or explicit alternatives ('for current conditions, use get_hawaii_weather'), so the conditional routing is left to inference.

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