DaedalMap Earthquake Data

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

The annotations already declare readOnlyHint=true, indicating a safe read operation. The description adds minimal behavioral context by noting 'Free discovery' and 'live agent-ready data packs,' which hints at real-time availability and accessibility, but doesn't disclose rate limits, authentication needs, or response format details. No contradiction with annotations exists.

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 highly concise and front-loaded, consisting of a single, efficient sentence that directly states the tool's function without unnecessary words. Every part of the sentence contributes to understanding the tool's purpose.

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 adequate but lacks details on output format (e.g., list structure, pagination) and differentiation from siblings. It covers the basic purpose but could be more complete by addressing usage context or behavioral traits beyond annotations.

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 input (none required). The description doesn't need to add parameter details, so it appropriately focuses on the tool's purpose. Baseline is 4 for zero parameters, as no compensation 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 clearly states the tool's purpose with a specific verb ('Returns') and resource ('list of live agent-ready data packs available on DaedalMap'), making it easy to understand what it does. However, it doesn't explicitly differentiate from sibling tools like 'get_pack' or 'query_dataset', which might offer similar data retrieval functions.

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 no guidance on when to use this tool versus alternatives. It mentions 'Free discovery' but doesn't clarify if this is for browsing available packs versus querying specific data, nor does it reference sibling tools like 'get_pack' for detailed pack information or 'query_dataset' for data queries.

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 indicate readOnlyHint=true. Description adds payment behavior (HTTP 402, USDC price) and distinguishes from preliminary upstream wrapper, which are valuable beyond the structured 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?

Four sentences covering key points: payment, lane, recommendation, cost advice. No redundancy, but could be slightly more structured with lists for clarity.

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 no output schema, the description covers when to use, payment mechanism, and lane choice. It could mention return format or example outputs, but overall provides sufficient context for an agent.

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 descriptions. The tool description does not add new parameter details beyond what is in the schema, but it reinforces the purpose of metrics and filters in context.

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?

Clearly states it queries the published earthquakes_events lane, distinguishes from sibling tools by calling itself the enriched DaedalMap history lane with stable loc_id, and mentions payment model.

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 'Use this first for earthquake questions' and explains how to handle payment (call without payment first, get 402 with price). Provides guidance on query breadth and cost.

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. The description adds useful behavioral context beyond that: it is a free wrapper calling USGS FDSN API, returns preliminary events, and normalizes to DaedalMap fields. This adds value without contradicting annotations, though it does not detail rate limits or data freshness.

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 exceptionally concise with four sentences, each adding value: first states identity, second gives usage condition, third warns what it is not. No filler, perfectly front-loaded.

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 11 parameters are fully documented in the schema, and the description provides clear purpose and usage guidance, the tool is fairly complete. However, the lack of an output schema means the description could have explained the normalized output format more, though it hints at it with 'normalized to DaedalMap event fields.'

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 each parameter having a clear description. The tool description does not add any additional parameter semantics beyond what the schema already provides, so 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 clearly states it fetches live preliminary earthquake events from USGS via the FDSN API, normalized to DaedalMap event fields. It explicitly distinguishes from the canonical earthquake lane by stating 'This is not the enriched canonical history lane,' providing clear differentiation from sibling tools like get_earthquake_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 explicitly specifies when to use the tool: 'only when the caller explicitly wants live/preliminary upstream results or needs a very recent window not yet present in the published canonical earthquake lane.' It also states what it is not. However, it does not explicitly name the alternative sibling tool (get_earthquake_events) for canonical data, only implying 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?

Beyond the readOnlyHint annotation, the description details what the tool returns (metadata, coverage, freshness, guidance, examples), adding valuable 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?

Two sentences, no waste, front-loaded with 'Free discovery.' Structure is efficient and clear.

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, the description explains what to expect (metadata, coverage, etc.) and when to use it, making it fully complete for a simple 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?

Schema provides full parameter description with examples. The description minimally adds by linking the parameter to the usage scenario, but doesn't significantly extend schema information.

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 about one pack, listing specific data types. It distinguishes itself from sibling tools like get_catalog by specifying pack-level detail.

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 calling this before querying a new pack, providing clear usage context. Lacks explicit exclusions but is still helpful.

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