DaedalMap Wildfire Events

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

The readOnlyHint annotation already covers safety, and the description adds minimal context (e.g., 'live' and 'agent-ready'). It does not detail output structure, pagination, or potential side effects, which is a gap given the absence of an output schema. However, for a zero-parameter read-only tool, the description is 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 two sentences: 'Free discovery.' and 'Returns the list of live agent-ready data packs available on DaedalMap.' It is front-loaded with a clear phrase, every word earns its place, and it avoids redundancy.

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 (no parameters, no output schema, read-only annotation), the description adequately covers the essential return value and context. It tells the agent exactly what to expect: a list of live, agent-ready data packs. No further details are necessary for this kind of discovery tool.

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 for parameter semantics is 4. No parameter details are needed, and the description correctly focuses on the return value. There is nothing to complain about here.

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 with a specific verb ('Returns') and resource ('list of live agent-ready data packs'). It distinguishes itself from sibling tools focused on disaster links and data queries, making its function obvious.

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' suggests a low-cost way to explore available data packs, but it does not explicitly mention when to use this tool over alternatives like get_pack or query_dataset. It provides clear context without exclusions, fitting the 'clear context, no exclusions' baseline.

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 include readOnlyHint=true, so the read-only nature is already declared. The description adds context about requiring an exact event id and producing a bounded chain, which is useful. However, it does not describe the return format, what 'bounded' means beyond the depth parameter, or any edge-case behavior. With the annotation covering safety, the description provides some additional value but not rich behavioral 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?

The description is brief and front-loads the core action: 'Expands one exact disaster event id into a bounded related-event chain.' It includes a usage guideline in the same breath. The opening 'Free linked-disaster helper' is slightly vague and could confuse, but it does not distract significantly. Overall, it is concise and well-structured, though not as tight as a pure two-sentence example.

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, the description does not need to explain return values, but it also does not hint at the structure of the 'chain' (e.g., nested events or flat list). The schema and annotations are thorough for parameters and safety, but the description is missing guidance on what the response looks like or any edge cases (ambiguous ids, depth behavior). This leaves some gaps for a tool that returns a possibly complex chain.

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 clearly described, including examples and defaults (e.g., event_id mentions 'NOAA-SIG-2', cross_type_only explains default true). The tool description adds little beyond what the schema already provides, mentioning 'supported pack' which is also in pack_id. Baseline 3 applies due to high schema coverage; the description does not meaningfully add parameter 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?

The description clearly states the tool's function: 'Expands one exact disaster event id into a bounded related-event chain.' It specifies the resource (exact disaster event id), the action (expands), and the output (bounded related-event chain). It also distinguishes from siblings by emphasizing it requires an exact id, unlike search_disaster_links, and by focusing on chain expansion rather than direct links.

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 a clear usage condition: 'Use this only when you already have an exact event id from a supported pack...' This tells the agent when to use the tool. However, it does not explicitly name alternative tools for cases where an exact id is lacking, nor does it state when not to use it in relation to siblings like search_disaster_links or get_disaster_links_for_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?

The readOnlyHint annotation already communicates the read-only safety profile. The description adds a little context (exact event id, published links) but does not disclose other behavioral traits like auth, rate limits, or output format. 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?

Two tight sentences: first sentence states purpose, second gives usage restriction. No filler, no 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 read-only resolver with 100% schema coverage, the description is adequate: it names the input condition and supported packs. It could more explicitly distinguish from get_disaster_link_chain or describe return shape, but these are not essential 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%, so all four parameters are already documented. The description reinforces that event_id must be exact and from a supported pack, but this largely repeats schema text rather than adding new meaning.

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 a specific verb ('resolves') and resource ('one exact disaster event id into its published related-disaster links'), with a scope boundary ('supported pack such as earthquakes, tsunamis, volcanoes, or wildfires'). This distinguishes it from broader search/list sibling tools like search_disaster_links.

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 an explicit usage condition: 'Use this only when you already have an exact event id from a supported pack.' This is clear context and a restriction, though it does not explicitly name alternative tools for other cases.

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 readOnlyHint=true already indicating a safe read operation, the description adds value by explaining the output nature: 'metadata, coverage, freshness, preferred canonical tool guidance, and first-query examples.' This clarifies that the tool is a discovery aid, not a data query, which is meaningful behavioral context beyond the annotation.

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 sentences, front-loads the key return values, and includes an actionable usage directive. Every word earns its place without redundancy.

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 1-parameter read-only tool with no output schema, the description sufficiently covers purpose, usage timing, and expected output contents. It could mention return format or error conditions, but given the low complexity, this is a minor 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?

The schema already provides 100% coverage with a detailed description of pack_id and examples. The description does not add any parameter-specific meaning beyond what the schema provides, so the baseline 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 clearly states the tool returns detailed metadata, coverage, freshness, canonical tool guidance, and first-query examples for one pack. This is specific and distinguishes it from siblings like get_catalog (which likely lists packs) and query_dataset (which queries actual 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 explicitly instructs to 'Call this before querying a new pack' to see time shape, coverage limits, and a paste-ready first query. This provides clear when-to-use context, though it does not explicitly name alternatives or excluded cases, so it falls short of a 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?

Annotations already declare readOnlyHint=true, so the agent knows the tool is safe and non-mutating. The description adds value by disclosing what the tool returns: 'when to use it, what it refuses, a working example, effective access limits, important outputs, provenance fields, recommended next calls, and the shared natural-language-to-strict-JSON interaction contract.' This gives a detailed picture of the tool's output behavior without contradicting the annotations. It doesn't mention potential errors (e.g., unknown tool name), but that's a minor 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 three sentences and front-loaded with purpose. The second sentence lists important output categories – a bit long but every item adds value. The final sentence gives a clear call-to-action. No fluff, but the list is dense. It earns its length and does not waste the reader's attention.

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, the description must explain return values, and it does by enumerating the content types. It also covers the discovery workflow and when to use the tool. It doesn't describe error behavior for invalid tool names, but given the low parameter count and simple purpose, the description is sufficiently complete for an agent to invoke the tool effectively.

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% – the only parameter 'tool_name' is described as 'Exact tool name from tools/list.' The description reinforces this by saying 'Use tools/list to discover names,' providing a helpful hint about the parameter's source. However, it adds no format, validation, or default information beyond what the schema already provides. The baseline of 3 applies because the schema fully documents the parameter.

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: 'Free blind-caller guidance for one tool visible on this MCP facade.' It uses a specific verb ('returns') and identifies the resource ('one tool'). It also lists concrete deliverables, distinguishing it from sibling tools that retrieve data (e.g., get_catalog, query_dataset). The purpose is unambiguous and front-loaded.

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 explicit workflow: 'Use tools/list to discover names, then call this before an unfamiliar tool.' This tells the agent when to use the tool and gives a clear prerequisite step. It does not explicitly state when not to use it, but the guidance is strong enough for an AI agent to select it appropriately. The mention of 'before an unfamiliar tool' signals a clear use case.

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 the read-only nature is already known. The description adds valuable context beyond annotations: the distinction between free and paid packs with a pricing mention (x402 Base USDC) alerts the agent to potential financial implications. It doesn't discuss rate limits or pagination, but the annotations cover the safety profile, so a 4 is justified.

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 concise and front-loaded with the core purpose. The pack list is necessary for guidance and is formatted as a comma-separated list that is easy to scan. No filler or redundant content; 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 tool with 8 parameters and no output schema, the description is minimal. It references the API contract as a substitute for explaining return values, which is somewhat helpful but not self-contained. It doesn't explain how to construct effective queries (e.g., combining filters and metrics) beyond the schema. Given the complexity, a more complete description would mention response format or invoke the contract explicitly. Thus, 3 is appropriate.

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%, so the baseline is 3. The description adds semantic value by listing valid pack_id examples and categorizing them as free or paid, which is not present in the schema. This helps the agent choose correct parameter values. However, it adds no extra detail on sort, filters, or metrics beyond what the schema already provides, so it doesn't exceed a 4.

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: 'Generic structured query for direct source_id or pack_id access'. This is a specific verb+resource combination that distinguishes it from sibling tools like get_catalog or get_pack, which likely return metadata rather than data. The mention of free vs paid packs further clarifies scope.

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 you have a specific source_id or pack_id and need structured data access, contrasting with catalog or metadata tools. It does not explicitly state when not to use it or name alternatives, but the 'direct source_id or pack_id access' phrasing provides clear situational guidance. The contract reference hints at API-level usage.

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 provide readOnlyHint=true, which covers the primary safety concern. The description adds that it is a 'Free linked-disaster discovery helper' and searches 'published' families, but does not disclose additional behavioral traits such as pagination, result shape, or what happens when no filters are provided. Given the read-only annotation, the bar is lower, but the description still lacks substantive behavioral 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?

The description is two sentences, front-loaded with 'Free linked-disaster discovery helper,' and every clause earns its place: it states what it does, the search criteria, and when to use it. 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?

For a read-only search tool with 7 optional parameters and no output schema, the description provides a clear purpose, a usage scenario, and a sense of what is returned (matching link families). It does not detail return values or edge cases, but the schema covers parameter constraints and the annotations cover safety. Missing output format details are a minor gap given the tool's discoverability focus.

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 having its own description. The tool description summarizes parameters as 'event-type direction, optional via-event type, and optional year window,' which adds little beyond the schema. Since the schema already fully documents each parameter, a baseline of 3 is appropriate and the description does not meaningfully enhance parameter understanding.

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 ('Searches') and resource ('published cross-disaster link families'), with clear filter dimensions: 'by event-type direction, optional via-event type, and optional year window.' It distinguishes from siblings by stating 'Use this when you want to discover whether a relationship family exists before you have an exact event id,' which contrasts with tools like get_disaster_links_for_event.

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 states when to use the tool: 'Use this when you want to discover whether a relationship family exists before you have an exact event id.' However, it does not explicitly name alternatives or provide 'when not to use' conditions beyond implying that having an exact event id changes the tool choice. This is clear but not fully explicit.

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