weather-intel-mcp

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

Description lists returned fields (magnitude, place, time, etc.) but lacks details on rate limits, authentication, or read-only nature; no annotations provided to fill gaps.

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 concise sentences, front-loaded with action, no redundant wording.

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?

Covered most parameters and output, but missing details on limit parameter and bounding box not reflected in schema; overall adequate for a simple list 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?

Adds meaning beyond schema by explaining filtering options and combining lat/lon/radius; schema covers 67% of parameters with descriptions, description compensates for remaining.

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 states it lists recent earthquakes from USGS feed, specifies filters (magnitude, days, location), and distinguishes from unrelated sibling tools like weather or elevation.

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?

Implied usage for earthquake data, but no explicit when-to-use vs siblings, though siblings are in different domains.

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?

No annotations provided, so description carries burden. Mentions data source (USGS) and output units (feet and meters) but does not disclose rate limits, error handling, or behavior outside US.

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, efficient and front-loaded with key information. No redundant or irrelevant content.

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?

No output schema, no annotations, and minimal parameter descriptions. Lacks return format details and error scenarios, though adequate for a simple coordinate-to-elevation 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 has 0% description coverage. The description does not add meaning to 'lat' and 'lon' beyond the tool's purpose, missing range constraints or format details.

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 the verb 'get', the resource 'ground elevation', and the geographic scope 'within the US'. Distinguishes from siblings which are about earthquakes, geocode, and weather.

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?

Implies usage for US locations only but does not explicitly state alternatives or when not to use. No guidance on coordinate system or accuracy limitations.

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?

No annotations provided, so description carries full burden. It explains the geocoding process using US Census. Lacks details like rate limits or authentication, but the behavior is simple and well-defined. Score 4 as it's very clear.

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 action and resource. Every sentence is essential and there is no wasted text.

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 only one required parameter, no nested objects, no output schema, and a simple task, the description fully covers what an agent needs to know: the purpose, usage context, and constraint (US only).

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 one parameter 'address' described. The description adds context: US street address format and an example. This adds meaningful information beyond the schema.

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 converts US street addresses to lat/lng coordinates, names the data source (US Census geocoder), and distinguishes itself by noting it's for weather/elevation tools. Specific verb 'convert' and resource 'address'.

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?

Explicit usage guidance: 'Use this first when you have an address but need coordinates for the weather/elevation tools. US addresses only.' Clearly states when to use and the constraint of US addresses.

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 discloses the type of alerts (warnings, watches, advisories) and return fields, but lacks details on potential behavioral traits like rate limits or authentication. A minor inconsistency exists between 'state or marine area' and focusing solely on state codes.

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 concise sentences: first states purpose, second provides example usage and expected output. No wasted words, 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?

For a simple single-parameter tool with no output schema, the description adequately covers purpose and output fields. It could mention that no output schema means the agent must parse the response, but overall it is 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?

With 100% schema coverage, the description adds marginal value by repeating the parameter info and providing examples. It does not explain marine area codes or clarify if they differ from state codes.

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 lists active NWS weather alerts for a US state or marine area, specifying the verb (list), resource (weather alerts), and scope. It is distinct from sibling tools like weather_current and weather_forecast.

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 clear context by instructing to pass a two-letter state code with examples. However, it does not explicitly state when not to use this tool or mention alternatives for weather 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves observed weather from the nearest NWS station, but does not mention data freshness, latency, API limits, or that the observation station may be distant from the given coordinates. The read-only nature is implied but not explicit.

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 sentence that efficiently conveys the tool's purpose, inputs, source, and outputs. It is front-loaded with the action and resource, with no extraneous 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?

For a simple tool with no output schema and no annotations, the description covers the essential purpose and inputs. However, it lacks details on potential distance from the station, update frequency, or whether the 'text description' is a weather summary. Given the sibling set, it distinguishes itself adequately but could be more informative.

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 0% description coverage for parameters. The description mentions 'latitude/longitude' but provides no additional details such as acceptable ranges (e.g., lat -90 to 90, lon -180 to 180), format, or that coordinates are required. Baseline is 4 for 0-parameter descriptions, but the description adds minimal value beyond the schema.

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 action 'Get', the resource 'latest observed weather conditions', the input method (latitude/longitude), and the data source (nearest NWS observation station). It lists output fields (temperature, humidity, wind, text description). It distinguishes itself from siblings like weather_forecast and weather_alerts by focusing on current observed conditions.

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 the tool is for current weather conditions, but lacks explicit guidance on when to use it versus alternatives. For example, it doesn't say 'Use for current observations; for forecasts use weather_forecast, for alerts use weather_alerts.' Users must infer from context.

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?

Describes output (named periods, temperature, wind, forecasts) and data source (NWS). Does not mention the optional hourly parameter or any limitations beyond US location. No annotations to supplement; description adequately covers read-only behavior but misses the hourly variant and 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 no wasted words. First sentence delivers purpose and input format; second gives actionable guidance. Efficient and 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?

No output schema or annotations; description covers main input/output but omits hourly option details and error handling. For a simple forecast tool, basic info is present but incomplete for all parameter scenarios.

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?

Only hourly parameter has a schema description; lat/lon lack schema descriptions. Tool description adds 'US location' context to lat/lon but not value ranges or format. With 33% schema coverage, description adds minor value but fails to fully compensate for missing param details.

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 gets a multi-day weather forecast for US locations via lat/lon and mentions returned data (named periods, temperature, wind, forecasts). It indirectly distinguishes from geocode by advising to use it first for addresses, but does not explicitly differentiate from weather_current or weather_alerts.

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?

Provides clear context: use when needing a multi-day US forecast by coordinates. Includes explicit guidance to use geocode for address conversion. Lacks explicit when-not-to-use (e.g., current conditions or alerts), but sufficient for basic usage.

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