DaedalMap Tsunami Data

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

Annotations already indicate readOnlyHint=true, so the agent knows this is a safe read operation. The description adds value by specifying 'live agent-ready data packs' (implying current, usable items) and 'Free discovery' (suggesting no cost or restrictions), but does not detail rate limits, authentication needs, or response format beyond the list.

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 front-loaded and highly concise with two clear phrases ('Free discovery' and 'Returns the list...'), each earning its place by setting usage context and specifying the output without any wasted words.

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 simplicity (0 parameters, read-only, no output schema), the description is mostly complete by stating the purpose and scope. However, it lacks details on the return format (e.g., structure of the list) or any limitations, which could be helpful despite the annotations covering safety.

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?

With 0 parameters and 100% schema description coverage, the schema fully documents the lack of inputs. The description adds semantic context by implying no parameters are needed for this discovery operation, aligning with the schema, but does not compensate for any gaps since there are none.

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 specific action ('Returns the list') and resource ('live agent-ready data packs available on DaedalMap'), distinguishing it from siblings like get_earthquake_events or query_dataset by focusing on catalog discovery rather than specific data retrieval or queries.

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 clear context for usage ('Free discovery' implies it's for exploring available data packs), but does not explicitly state when not to use it or name alternatives among siblings, such as get_pack for specific pack details.

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, indicating a safe read operation. The description adds context by specifying the return content (metadata, coverage, metrics, guidance) and noting 'Free discovery,' which implies no cost or restrictions. It doesn't disclose additional behavioral traits like rate limits or authentication needs, but with annotations covering safety, 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, efficient sentence that front-loads key information ('Free discovery') and clearly states the tool's function. Every word earns its place, with no redundancy or unnecessary elaboration.

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 (1 parameter, read-only, no output schema), the description is reasonably complete. It specifies what the tool returns, though it could benefit from more detail on output structure or examples. With annotations covering safety, it provides adequate context for agent use.

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%, with the parameter 'pack_id' fully documented in the schema. The description doesn't add any parameter-specific details beyond what the schema provides, such as examples or usage tips. Baseline 3 is appropriate when the schema handles parameter documentation.

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 purpose: 'Returns detailed metadata, coverage, metrics, and first-query guidance for one pack.' It specifies the verb ('Returns') and resource ('detailed metadata... for one pack'), though it doesn't explicitly differentiate from sibling tools like 'get_catalog' or 'query_dataset'.

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 context with 'Free discovery' and 'first-query guidance,' suggesting this is for initial exploration of a pack. However, it lacks explicit guidance on when to use this tool versus alternatives like 'get_catalog' (for listing packs) or 'query_dataset' (for querying data).

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?

The description adds some behavioral context beyond the readOnlyHint annotation. It specifies this queries for 'tsunami source events and related metrics', which gives domain context. However, it doesn't mention rate limits, authentication requirements, pagination behavior, or response format details. With annotations covering the read-only aspect, the description adds moderate but incomplete behavioral transparency.

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 appropriately concise at two sentences. The first sentence establishes the paid nature and core function, while the second specifies the target data and purpose. There's no wasted verbiage, though the structure could be slightly improved by front-loading the core functionality more clearly.

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 query tool with readOnlyHint annotation and comprehensive schema coverage, the description provides adequate but minimal context. It identifies the domain (tsunami events) and mentions it's a paid tool, but lacks information about typical use cases, response structure, or how this differs from sibling query tools. Without an output schema, some description of return values would be helpful.

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?

With 100% schema description coverage, the schema already documents all 6 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions 'metrics' and 'filters' in a general sense but provides no additional syntax, format, or usage guidance. This meets the baseline 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 clearly states the tool 'queries tsunamis_events for tsunami source events and related metrics', providing a specific verb ('queries') and resource ('tsunamis_events'). It distinguishes from some siblings like 'get_fx_rates' or 'get_pack' by specifying the tsunami domain, but doesn't explicitly differentiate from similar query tools like 'get_earthquake_events' or 'query_dataset'.

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 minimal usage guidance. It mentions this is a 'Paid x402 tool' which implies cost considerations, but gives no explicit guidance on when to use this tool versus alternatives like 'get_earthquake_events' or 'query_dataset'. There's no mention of prerequisites, typical use cases, or when-not-to-use scenarios.

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