nws-weather-mcp-server

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

The annotation readOnlyHint=true already declares the tool is read-only, and the description does not contradict this. The description adds behavioral context by noting the results are sorted by proximity and include distance and bearing, which is useful but not extensive. Since annotations cover the safety profile, the description adds moderate value but doesn't go deeper into response format or edge 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?

The description is two sentences with zero wasted words. The primary purpose is front-loaded, followed by the output format and a clear usage pointer. It is compact yet informative, making it easy for an agent to parse quickly.

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 that an output schema exists and parameter descriptions are fully covered in the input schema, the description only needs to convey purpose and usage, which it does thoroughly. It explains the discovery workflow and the relationship to a sibling tool, so nothing essential is missing for correct invocation.

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% and every parameter (latitude, longitude, limit, cursor) already has a detailed description in the schema. The description itself does not add additional parameter 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 verb 'Find', the resource 'weather observation stations', and the spatial scope 'near a location'. It also mentions the output order (by proximity with distance and bearing) and links to a specific consumer (nws_get_observations), making it distinct from sibling tools like forecasts, alerts, and discussions.

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 to discover station IDs for nws_get_observations.' This gives clear context and implies a specific workflow. While it doesn't explicitly mention alternatives or when not to use it, the linkage to a sibling tool and the distinct purpose provide adequate guidance for an agent to select it correctly.

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 tool is known to be safe and non-mutating. The description adds the information that two output modes exist (named 12-hour periods or hourly), but this is already fully documented in the 'hourly' parameter schema. Since the description contributes little beyond what annotations and schema already convey, a score of 3 is appropriate.

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, well-formed sentence that front-loads the primary purpose and immediately follows with the key behavioral distinction (two output formats). Every word carries meaning, with no filler or 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 that the schema fully documents parameters, the output schema exists, and the read-only annotation is present, the description is sufficient for an agent to invoke the tool correctly. The only minor gap is that it does not explain pagination behavior, but that is handled in the cursor parameter description, so completeness is good. A slight deduction for the lack of any mention of how to handle the hourly vs named-period choice in context.

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 provides 100% description coverage for all four parameters, including format details for latitude/longitude and the meaning of 'hourly' and 'cursor'. The description does not add any new parameter context beyond what the schema already states, so the baseline of 3 applies.

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 weather forecast') and the resource ('a US location'), and it adds the distinguishing detail of returning either 12-hour named periods or hourly breakdowns. This makes the tool's purpose explicit and differentiates it from sibling tools like observations or office discussion without ambiguity.

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 such as nws_get_zone_forecast or nws_get_observations. It does not mention any exclusions, prerequisites, or hints about choosing between forecast modes. An agent must infer usage context from external knowledge, which is a significant gap given the sibling toolset.

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?

ReadOnlyHint is true and the description does not contradict it (says 'get', a read operation). Beyond the annotation, it discloses a key behavior: automatic nearest-station resolution when coordinates are provided. This adds meaningful context beyond the schema and annotations, justifying a 4.

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?

A single sentence that front-loads the core purpose and then covers both input methods without any redundant words. Every phrase contributes value, and it is immediately scannable.

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 tool with a full output schema and 100% parameter documentation, the description covers the essential usage: giving coordinates or a station ID. It does not explicitly mention that station_id overrides coordinates (though the schema does) or that only one input method should be used, but that is covered structurally. Overall, an agent has enough to call it correctly.

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% and each parameter already has a clear description (e.g., latitude says 'for automatic station resolution'). The description adds no new parameter semantics beyond an example station ID and a pointer to nws_find_stations, which the schema already implies. Baseline 3 is appropriate when the schema fully documents 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?

States the specific verb 'Get' and resource 'current weather observations', with the parenthetical 'actual measured conditions' clearly differentiating from forecast tools. The description also names both input methods (coordinates and station ID), making its scope unambiguous.

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 when to use it (for current measured conditions rather than forecasts) and references nws_find_stations for station ID discovery, but does not explicitly contrast with sibling tools like nws_get_forecast or state when *not* to use it. The context is clear, but explicit alternatives are missing, 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 tool is known to be a safe read operation. The description does not contradict this. It adds context about product types, which is more about output content than behavior. It does not disclose any potential side effects (none expected), rate limits, or error conditions, but given the read-only nature and output schema availability, this is acceptable but not enriched 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 concise, starting with the primary purpose and then enumerating product types with brief explanations. Each sentence earns its place, and no fluff or redundancy exists. The structure front-loads the core function and flows logically to supporting 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?

The tool has an output schema, so return formats are covered there. The description covers the essential parameters and product types, and mentions the source of the office code. It is complete for a simple read-only tool. It could theoretically mention that the output is free text, but that is implicit and handled by the output schema. Overall, nothing critical is missing.

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 both parameters (office and product_type) having detailed descriptions in the schema. The description repeats the product type explanations, adding little beyond the schema. The only additional value is the mention that office comes from nws_get_forecast, but the schema already says that. Since the schema carries the load, the description does not meaningfully enhance parameter understanding, so a 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: retrieving the latest narrative forecast product from a WFO. It names the default product (AFD) and lists the other product types, distinguishing it from siblings like nws_get_forecast (which likely provides structured forecast data) and nws_get_zone_forecast (which may return similar text but focused on zones). The verb 'get' and resource 'office discussion' are specific and unambiguous.

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 context on when to use the tool by explaining what each product type is (e.g., AFD explains reasoning, HWO is an outlook, etc.). It also references nws_get_forecast as the source for the office code, which is helpful for chaining. However, it does not explicitly state when to prefer this over nws_get_zone_forecast or other siblings, leaving that to inference from the product descriptions. Still, the guidance is clear enough for an agent to decide.

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, and the description does not contradict this. The description adds meaningful behavioral context: it describes the return content (named periods, narrative text), the constraint that only 'forecast' type zones resolve, and the zone code pattern. This goes beyond the annotation without being excessive, though it omits potential error behaviors or rate limits, which are not critical given the read-only nature.

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 moderately long but every sentence carries useful information: primary purpose, return structure, integration hints, and a usage constraint. It is front-loaded with the core purpose and then elaborates. There is minimal redundancy; the only slightly verbose part is the explanation of the alert-to-forecast chain, but that is directly relevant for correct parameter selection.

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?

The description covers the essential aspects: what the tool does, how to obtain a valid parameter, what constraints exist, and the nature of the output. Since an output schema exists, the return format need not be fully explained. While it doesn't explicitly list alternate tools for comparison, it gives enough context to avoid confusion. The integration with sibling tools is well documented, making it complete for an agent's selection and invocation.

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%, providing a clear baseline. The description adds extra semantic value by explaining the zone ID pattern ('XXZ###'), giving a concrete example, and specifying how the ID can be obtained from other tools (as 'forecastZone' or from 'affectedZones'). This context helps the agent correctly construct the parameter beyond what the schema alone offers.

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 a specific verb ('Get'), resource ('text forecast for a public NWS forecast zone'), and outcome (returns named periods with narrative text). It also gives concrete examples of zone codes and clearly distinguishes the zone-level forecast from other forecast types, making the tool's role unambiguous even among siblings like nws_get_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 explains how to obtain a valid zone_id from sibling tools (nws_search_alerts, nws_find_stations) and explicitly restricts usage to affectedZones entries with type 'forecast', excluding 'county' and 'fire' types. While it doesn't explicitly compare to nws_get_forecast, it provides clear context for when this tool should be used, and the exclusion of non-forecast types gives actionable guidance.

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 signals that this is a safe read operation. The description adds the specific behavioral context that the tool returns a list of alert type names, which is beyond the annotation's binary read-only signal. While it does not mention rate limits or authentication, those are not critical for a simple listing tool, and the annotation covers 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 three short, purposeful sentences. The first states the core action, the second gives usage context, and the third clarifies the lack of parameters. There is no fluff or redundancy, and the most important detail is 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 parameterless, read-only list tool, the description is complete. It explains what the tool returns (alert event type names), why it is used (to feed the event filter in nws_search_alerts or to browse), and that it requires no inputs. The output schema (present but not shown) would cover return format details, so nothing is missing from the description.

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 zero parameters, the rubric sets a baseline of 4. The description's note 'No parameters required' reinforces what the empty schema already implies but does not contradict it. There is nothing more to explain about params since none exist.

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 opens with a specific verb and resource: 'List all valid NWS alert event type names.' It clearly distinguishes this tool from siblings by stating its purpose is to provide valid values for the event filter in nws_search_alerts. This removes any ambiguity about what the tool does and its place among the sibling tools.

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 to discover valid values for the event filter in nws_search_alerts, or to browse alert categories.' It gives a clear primary use case tied to a sibling tool, and a secondary browsing use, leaving no doubt about when an agent should invoke 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?

Annotations only declare readOnlyHint=true; the description takes on the burden of behavioral detail. It discloses non-obvious behavior: case-insensitive/partial event matching, pagination mechanics (cursor carries its own page size, limit applies only to first page), and that each call re-fetches /alerts/active so results are contiguous within a response but not across calls. This is exactly the kind of context an agent needs.

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 long but every sentence earns its place. The core purpose and filter list come first, followed by the mutual-exclusivity rule and the national-search fallback. It avoids repetition and packs the most critical operational details (pagination, event matching) into the schema descriptions, which is appropriate. Slight verbosity in listing every filter type, but it's a complex tool.

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 12 optional parameters and an output schema, the description covers all necessary operational aspects: the search scope, how each filter works, mutual exclusivity, pagination, and how to handle the cursor. It cross-references nws_list_alert_types for event discovery, which closes a potential knowledge gap. Nothing an agent needs to call this correctly is missing.

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, but the description adds substantial value beyond the schema: clarification of event matching (case-insensitive, partial), the meaning of totalCount with small limits, the behavior of cursor tokens, and the interpretation of region codes. It also reinforces the mutual-exclusivity rule for the group of parameters. This transforms ambiguous filters into actionable guidance.

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 opens with a specific verb+resource: "Search active weather alerts (watches, warnings, advisories) across the US." It immediately distinguishes the tool from siblings like nws_get_forecast or nws_get_observations. It also clearly enumerates filter dimensions, leaving no doubt about 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?

Provides clear context: how to filter (state, coordinates, zone, etc.), states the mutual-exclusivity rule, and explicitly covers the national-search case ("Omit all filters"). It points to nws_list_alert_types for discovering valid event names. It doesn't explicitly name alternatives or say when not to use this tool, but the sibling tools are different enough that this is unnecessary.

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