api

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

With no annotations provided, the description must disclose behavior on its own. It states that the tool returns events with geographic footprints grouped by disaster type, which gives useful behavioral context, but does not explain how 'active' is defined or how filtering (eventTypes) affects results.

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 that immediately states the tool's purpose and return information. No wasted words or repetition of schema 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?

For a simple tool with one optional parameter and no output schema, the description adequately explains what it returns (events with geographic footprints grouped by type). It lacks detail on edge cases or definition of 'active', but this is minor for the tool's simplicity.

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 100% of parameter descriptions (eventTypes already explained in the input schema). The tool description adds no additional parameter semantics, so a baseline score 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 uses a specific verb ('Get') and resource ('currently active disasters'), clearly distinguishing from siblings like get_recent_alerts or search_events by focusing on active status and geographic footprints grouped by disaster type.

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 'currently active' provides clear context for when to use this tool, but it does not explicitly mention alternatives or exclusions. No explicit 'when to use vs other tools' guidance, but the active-disaster scope is unambiguous.

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 burden. It correctly implies a read-only informational operation, but it does not disclose the output format (e.g., string, list) or whether the explanation covers all GDACS levels or only some. The behavior is simple enough that this is adequate, but not richly transparent.

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 redundant words. It immediately states the action and the resource, achieving maximum conciseness without losing meaning.

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, no-output-schema tool of low complexity, the description is sufficient to understand its purpose. However, it could slightly benefit from specifying exactly what the explanation includes (e.g., color codes, numeric levels), but this is a minor gap given the tool's simplicity.

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 has zero parameters, so the baseline is 4. The description adds no parameter-specific detail, which is acceptable since there is nothing to document beyond 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?

The description clearly states it returns an explanation of GDACS alert level classifications and their meanings. This is a specific verb+resource phrasing that distinguishes it from sibling tools focused on disasters, statistics, or 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?

The description implies the tool is for understanding alert level classifications, but it does not explicitly state when to use it over alternatives or provide exclusion conditions. Usage context is implied rather than articulated.

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 are provided, so the description carries the full burden. It only restates the grouping dimensions without adding behavioral context such as return format, whether it includes empty groups, or any limitations. The description adds no information beyond what the tool name and schema already convey.

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 concise sentence that is front-loaded with the verb 'Get' and contains no redundant information. Every word adds value.

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 no annotations, the description should explain the return structure or data shape. It does not specify what 'disaster statistics' includes (e.g., counts, totals, per-group breakdowns). Given the tool's moderate complexity (5 optional parameters), this is a significant gap.

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 individual parameter descriptions, but the tool description adds meaning by clarifying the relationship: eventTypes and alertLevel are aggregation dimensions, and fromDate/toDate define the time period. This synthesizes the parameters into a coherent purpose, exceeding what the schema provides.

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's function: 'Get disaster statistics aggregated by event type and alert level for a specified time period.' It uses a specific verb and resource, and the aggregation dimensions (event type, alert level, time period) distinguish it from siblings like search_events or get_active_disasters.

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 implies usage for aggregated statistics but does not explicitly mention when to use this tool versus alternatives or provide exclusions. Sibling tool names suggest alternatives, but no direct comparison or 'use instead' guidance is given.

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 are provided, so the description must carry the full burden for behavioral disclosure. It only states what data is returned (location, severity, affected population, timeline) without mentioning side effects, error behavior, data freshness, external API calls, or any limitations. For a read tool, some baseline safety is assumed, but the lack of explicit behavioral context is a gap.

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 starts with the action and resource, then briefly lists the key returned data fields. Every word adds value, with no filler or redundancy. It is effectively structured and immediately scannable.

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?

There is no output schema, so the description must convey what the response contains. It lists several return fields but does not explain the full response structure or why both eventType and eventId are required. It also lacks context on how this tool fits with siblings, leaving some ambiguity for an AI agent unfamiliar with the domain.

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 complete descriptions for both parameters (eventId, eventType), giving 100% schema coverage. The description does not add any parameter-specific meaning beyond the schema, such as how eventType and eventId interact or the format of eventType codes. According to the rubric, a baseline of 3 is appropriate when the schema handles the heavy lifting.

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 verb 'Get' and the resource 'detailed information about a specific disaster event.' This directly distinguishes it from siblings like get_active_disasters or get_recent_alerts, which list events rather than fetch details for a single identified event. The mention of 'specific' event is a strong differentiator.

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 implies usage when a user needs details for a known event, but it does not explicitly state when to use this tool versus alternatives such as search_events or get_active_disasters. There is no direct exclusion or comparison with sibling tools, so the guidance is only implied through the phrase 'specific disaster event.'

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 burden. It claims 'all' events, but the schema includes a limit parameter (default 50, max 100), making the claim misleading. It also fails to disclose the default 30-day lookback period or the meaning of 'affecting,' leaving key behavioral aspects undocumented.

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 unnecessary words. It states exactly what the tool does, making it highly concise and easy to parse.

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?

Without an output schema or annotations, the description must compensate by explaining result limits, time-window defaults, and the criteria for 'affecting.' The one-line description omits these critical details, leaving the tool underspecified for an AI agent to use 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 covers all 3 parameters with detailed descriptions (100% coverage). The tool description adds no additional parameter-level meaning, so the baseline of 3 is appropriate since the schema does the heavy lifting.

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+resource+scope: 'Get all disaster events affecting a specific country.' This clearly distinguishes it from siblings like get_active_disasters (active disasters) and search_events (general search), making the tool's purpose unambiguous.

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 implies usage for country-filtered queries but does not explicitly state when to use this tool over alternatives like search_events. No exclusions or alternative recommendations are provided, so usage context is only implied.

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 provided, the description carries the full burden. It states that the tool returns a list of all supported event types with descriptions, which implies a read-only, full-list behavior. However, it does not disclose anything else like authentication requirements, response format, or potential limitations, but for a simple parameterless list tool, this is adequate.

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, concise sentence with no redundant words. It is front-loaded with the action and clearly states the outcome. 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?

Given the tool's low complexity (no parameters, no output schema, no annotations), the description fully covers what an agent needs to know: what the tool returns and that it covers all supported types. No additional information is necessary to invoke it 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 0 parameters, and the description doesn't need to add parameter semantics. Per the rubric, 0 parameters gets a baseline of 4. The description adds no parameter info, but none 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 uses a specific verb ('Get'), a resource ('list of all supported disaster event types'), and adds scope ('with their descriptions'). This clearly distinguishes it from sibling tools like get_active_disasters or get_alert_level_info, which focus on different data.

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 implies its use case: to retrieve the catalog of supported event types. However, it provides no explicit 'when to use' or alternatives, nor any guidance on how this tool relates to siblings. The context is clear but not explicitly 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?

No annotations are provided, so the description carries the full burden. It discloses the temporal scope and that the result is a list, but does not mention sorting, empty result behavior, or the filtering effect of minAlertLevel. This is minimal but not misleading.

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 states the purpose without redundancy. Every word contributes meaning, making it highly concise and well-structured.

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 tool with two optional parameters and no output schema, the description is minimally adequate. It clearly states the tool's function but omits return format details and the behavior of minAlertLevel, relying on the schema to fill these gaps.

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 100% coverage with descriptions for both 'hours' and 'minAlertLevel', including defaults and valid values. The description adds no additional parameter context, aligning with the baseline of 3 for 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 uses a specific verb 'Get' with a clear resource ('list of recent disaster alerts') and a temporal scope ('last N hours'). This distinguishes it from sibling tools like get_active_disasters (active vs. recent) and search_events (search vs. list).

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 implies the tool is for retrieving recent alerts within a time window but does not explicitly state when to use it over alternatives like get_active_disasters or search_events. There are no stated exclusions or alternative tool references.

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 are provided, so the description bears the full burden. It does disclose the ordering behavior and that it returns a list, but it omits how filters combine (e.g., AND/OR), pagination behavior, and whether any filters are required, which are important behavioral traits for a search 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?

Two sentences, immediately states the verb and resource. No filler or redundant restatement of schema fields. The word count is appropriate for the tool's complexity.

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?

While the schema thoroughly covers parameters, the description lacks information about response format, filter combination logic, and default behavior (e.g., what happens with no filters). With no output schema and no annotations, the description is too sparse to fully prepare an agent to invoke the tool effectively, but it does convey the core search and ordering semantics.

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 100% coverage, with descriptions for all 8 parameters (limit, dates, country, eventname, alertLevel, eventTypes, minSeverity). The description adds no additional parameter semantics beyond listing 'various filters', so it doesn't exceed the schema 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 the specific verb 'Search' and states the resource ('disaster events') and output behavior ('returns a list of events matching the criteria, ordered by date descending'). It does not explicitly differentiate from sibling tools like get_events_by_country or get_recent_alerts, but the emphasis on arbitrary filters makes its scope clear.

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?

There is no guidance about when to prefer this tool over alternatives such as get_recent_alerts or get_events_by_country. The description only says 'various filters' without explaining trade-offs, so the agent gets no decision support.

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