DaedalMap Hurricane and Tropical Cyclone Data

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

Annotations already declare readOnlyHint=true, and the description adds 'Free discovery' to convey that no cost or auth is needed. It does not detail return format or error behavior, but for a parameterless read-only operation, the provided context 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 two concise sentences: 'Free discovery. Returns the list of live agent-ready data packs available on DaedalMap.' Every phrase adds value, with the purpose front-loaded and no fluff.

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 parameterless read-only tool, the description sufficiently explains what it returns and adds platform context. It does not elaborate on the structure of 'data packs' or output format, but given the lack of an output schema and the tool's simplicity, the description is nearly 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 tool has zero parameters, and the schema covers 100% of parameters vacuously. Per the rubric, a baseline of 4 is appropriate when there are no parameters, and the description adds no unnecessary detail about parameters.

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: 'Returns the list of live agent-ready data packs available on DaedalMap.' This specifies the verb (Returns), the resource (list of data packs), and the platform, distinguishing it from siblings like get_pack and 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 phrase 'Free discovery' and the description of returning the catalog make it clear this is the tool for listing available data packs, not for querying or searching. However, it does not explicitly mention alternatives or exclusions, so it stops short of a full 5.

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?

Beyond the readOnlyHint annotation, the description discloses what the tool returns (detailed metadata, coverage, freshness, etc.) and frames it as 'Free discovery'. This adds context about the tool's behavior and output value, though it doesn't discuss rate limits or error cases.

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 front-loaded purpose and a clear usage directive. Every word earns its place; no filler.

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 single-parameter, read-only tool without an output schema, the description covers the key information: what it returns, why to use it, and how it informs querying. It could mention return format, but the listed output categories are sufficient.

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 already fully describes pack_id with 100% coverage, including example values. The description only reiterates that it's for one pack, adding no new parameter-level information. 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 states 'Returns detailed metadata, coverage, freshness, preferred canonical tool guidance, and first-query examples for one pack', which clearly specifies the action and resource. It also differentiates from query tools by advising to call before querying a new pack.

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 'Call this before querying a new pack so you can see time shape, coverage limits, and the paste-ready first query', giving clear when-to-use guidance. It doesn't explicitly mention when not to use or name alternatives, but the context strongly implies it's for pre-query discovery.

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, so safety is known. The description augments this by detailing the return payload and the interaction contract. It doesn't describe failure behavior on invalid tool_name, but that's not critical for a read-only help 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, front-loaded with purpose, packed with useful detail without padding. 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?

For a one-parameter read-only helper, the description tells what to expect in the response and how to use it. It lists the response contents, so no output schema is needed.

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 covers tool_name 100% with a clear description ('Exact tool name from tools/list'). The description adds usage context (call before unfamiliar tool) but no additional syntax requirements, 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?

The description clearly states the tool returns guidance for any visible tool, listing specific content types (when to use, refusals, example, limits, outputs, provenance, next calls, interaction contract). This distinguishes it from sibling data tools (get_catalog, search_disaster_links) as a meta-help tool.

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 instructs to call tools/list first, then call this before unfamiliar tool. This gives a clear when-to-use policy and a workflow. Sibling tools are for data, so no confusion about alternatives.

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 annotation readOnlyHint=true already establishes the safe read nature. The description adds value by referencing the exact API contract (POST /api/v1/query/dataset) and explicitly distinguishing free vs. paid packs (x402 Base USDC), which are behavioral constraints beyond the annotation. It doesn't dwell on return format or side effects, but the read-only behavior is covered.

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 concise sentences that front-load the primary purpose and then list the supported free and paid packs. Every sentence provides necessary context without filler or repetition.

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 8 parameters, no output schema, and readOnly annotation, the description supplies a high-level contract reference and pack list, which complements the detailed schema. It lacks an explicit description of return values, but the API contract reference partially addresses this. Overall, it's fairly complete for a query tool with comprehensive schema documentation.

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 8 parameters, so the schema already documents each parameter. The tool description only repeats source_id and pack_id concepts already in the schema and adds no new parameter semantics. Baseline of 3 is appropriate since 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 clearly identifies the tool as a 'Generic structured query for direct source_id or pack_id access' with a specific API contract. This distinguishes it from siblings like get_catalog or get_pack, which are for metadata and catalog discovery, by focusing on actual data retrieval.

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 context that this tool is used for querying data by source_id or pack_id and lists the available free and paid packs, implying it's for known data sources. It does not explicitly mention alternatives or exclude cases, but the context is clear enough for an agent to infer when to use it.

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 readOnlyHint annotation already communicates that this is a safe read operation, so the description only needs to add extra context. It adds the discovery-oriented behavior ('discover whether a relationship family exists') but doesn't disclose pagination, result ordering, or limitations. This matches the expected baseline when annotations cover safety.

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 only two sentences, with the purpose front-loaded in the first sentence and the use case in the second. Every word earns its place, and there is no redundancy or filler.

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 moderate complexity (7 optional parameters, no output schema), the description sufficiently explains the discovery scenario and the available filtering dimensions. It does not describe the return value shape, but for a search/discovery helper, the purpose and use case are clearly communicated, leaving only minor 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?

Schema description coverage is 100%, with each parameter (limit, year_start, year_end, event types) well-documented. The description's mention of 'event-type direction' and 'year window' aligns with the schema but doesn't add new semantic meaning beyond what the parameter descriptions already provide. 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 the tool's function: 'Searches published cross-disaster link families by event-type direction, optional via-event type, and optional year window.' It uses a specific verb ('searches') and resource ('link families'), and the context of discovery ('before you have an exact event id') distinguishes it from sibling tools like get_catalog.

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?

It provides clear guidance on when to use: 'Use this when you want to discover whether a relationship family exists before you have an exact event id.' However, it does not explicitly state when not to use it or mention alternative tools, so it stops short of a full when/when-not/alternatives breakdown.

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