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 declare readOnlyHint=true. Description adds value with specifics about return content (metadata, coverage, etc.) and reinforces non-destructive nature. No contradictions.

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, front-loaded with 'Free discovery', no superfluous words. Efficient and clearly 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?

Given the simple interface (1 param, no output schema), the description fully covers what the tool does, what it returns, and when to use it.

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 parameter description already listing possible pack_ids. Description adds minimal extra meaning beyond restating 'one pack'. 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?

The description clearly states it returns detailed metadata, coverage, freshness, tool guidance, and first-query examples for one pack. It distinguishes from siblings: get_catalog (list all packs) and get_tsunami_events (specific pack 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 advises 'Call this before querying a new pack' and explains the benefits. Does not explicitly state when not to use, but context is clear.

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?

Description discloses critical behavior beyond readOnlyHint: it's a paid tool that returns HTTP 402 with the price before charging. This is essential for correct agent invocation. No contradiction 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?

Three sentences deliver purpose, usage guidance, and payment behavior without redundancy. Information is front-loaded and every sentence 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?

Despite no output schema, description provides enough expectation of return data (historical records, wave-height metrics, specific metrics). Payment workflow is explained. For a moderately complex tool with 6 parameters, the description covers key aspects well.

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%, but description adds significant value with examples (e.g., 'event_count', 'max_water_height_m' for metrics) and usage advice (e.g., narrowing time range for sort-intensive queries). This goes beyond basic schema descriptions.

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?

Description clearly states 'Queries tsunamis_events for historical tsunami records and wave-height metrics', using a specific verb and resource. It distinguishes from siblings (get_catalog, get_pack) by focusing solely on tsunami events, and adds context about metrics and region filters.

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?

Description specifies best use cases ('event counts, max water height thresholds, top-event lookups') and provides filter guidance (ISO3 or XOO region IDs). It also advises on payment workflow ('call without payment first'). While it doesn't explicitly list when not to use, the context is clear and helpful.

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