Server Quality Checklist

Tool Scores

• get_hourly_historyA
  3.9/5.0
  Behavior3/5

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

  The description adds context beyond the input schema by listing returned data fields (temperature, humidity, wind, precipitation). Since no annotations are provided, the description carries the burden. It does not disclose potential rate limits, data freshness, or whether historical data beyond 24 hours is unavailable. The behavior is largely inferred as a read-only query.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness4/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single sentence that conveys the purpose, scope, and key data fields. It is front-loaded and efficient, though it could be slightly more concise by removing the repeated station ID in parentheses.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's low complexity (1 optional parameter, no output schema needed for a simple data list), the description covers the essential information. It lacks return format details but is sufficient for an agent to understand what data it will receive.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The schema already provides 100% coverage with a clear description for the 'hours' parameter (range 1–24, default 24). The description adds no further parameter details, so the baseline of 3 applies. It does not explain what happens if hours is omitted or out of range.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description specifies a clear verb ('Get'), resource ('hour-by-hour weather history'), scope ('up to the last 24 hours'), station ID, and data fields (temperature, humidity, wind, precipitation). This differentiates it from siblings like 'get_current_conditions' (single snapshot) and 'get_daily_summary' (daily aggregates).

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies when to use this tool (to get detailed hourly history for the past 24 hours). It contrasts with siblings by mentioning hour-by-hour granularity and specific fields. However, it does not explicitly state when not to use it or mention alternatives for longer periods.

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

• get_daily_summaryA
  4/5.0
  Behavior4/5

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

  No annotations exist, so the description must disclose behavior. It specifies the exact data returned (temperature, precipitation, wind gust) and the station identifier, which adds transparency. However, it does not mention data availability guarantees or any quirks.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  Single sentence that is concise and front-loaded with the key verb and resource. No extraneous information.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the simple schema (1 optional param), no output schema, and no annotations, the description is reasonably complete. It covers what data is returned and the time range. Could mention that data is from a specific station, but it already does.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 100%, so baseline is 3. The description adds context by stating 'up to the last 7 days' but does not elaborate on the default behavior (default 7 days) beyond what the schema says.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  Clearly states the verb 'Get' and specific resource: daily high/low/avg temperature, precipitation, and wind gust for a specific station. It includes the station ID and the time range (up to 7 days). This differentiates it from siblings like get_current_conditions (current) and get_hourly_history (hourly).

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies usage for historical daily summaries, but provides no explicit guidance on when to use this vs. alternatives like get_hourly_history. No mention of when not to use it or limitations beyond the 7-day max.

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

• get_current_conditionsA
  4.2/5.0
  Behavior4/5

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

  With no annotations provided, the description clearly communicates this is a read-only operation (get current conditions). It lists the return fields, giving the agent a good understanding of what to expect. No contradictions.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is two sentences, front-loading the purpose and then listing the return fields. Every word is useful and no filler.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given zero parameters and no output schema, the description adequately explains what the tool returns. It could mention that data is from a specific station (KCALAKEF92) which it does. Without an output schema, listing fields is helpful. A minor gap: it doesn't note if data is live or cached, but overall complete enough.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The input schema has zero parameters and 100% schema description coverage, so the description does not need to add parameter info. Baseline 3 is appropriate.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states it returns current weather conditions from a specific personal weather station, listing exactly which metrics (temperature, humidity, etc.). It uniquely identifies the resource and action, distinguishing it from siblings like get_daily_summary.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies this is for current, real-time conditions versus historical or summary data, which differentiates it from siblings. However, it does not explicitly state when not to use it or provide alternatives.

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

• get_station_infoA
  4.2/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the full burden. It discloses that the tool returns metadata (name, ID, location, elevation) and is specific to one station, but does not mention any side effects, data freshness, or access requirements. Since there are no annotations to contradict, a 3 is appropriate for a read-only metadata tool.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single sentence with no wasted words, clearly stating the action and listing the returned fields. It is front-loaded and efficiently communicates the tool's purpose.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool has zero parameters, no output schema, and no annotations, the description covers the essential information: what it does, which station, and what data it returns. It could optionally mention if the data is static or dynamic, but the current description is sufficient for an agent to use the tool correctly.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The input schema has no parameters and schema description coverage is 100%, so the description need not add parameter info. The description's mention of the specific station and the fields returned provides useful context beyond the empty schema.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly specifies the verb 'Get' and the resource 'metadata for the KCALAKEF92 weather station', listing exactly which fields are returned (name, ID, neighborhood, country, GPS coordinates, elevation). It distinguishes from siblings like get_current_conditions and get_daily_summary which focus on weather data rather than station metadata.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description explicitly names the station (KCALAKEF92) and states it returns metadata, implying it's for station information rather than weather data. However, it doesn't explicitly say when not to use it or compare to siblings, though the station-specific nature and listed fields make the context clear.

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