Server Quality Checklist

Tool Scores

• get_port_congestionA
  4.4/5.0
  Behavior4/5

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

  With no annotations, the description carries the full burden. It transparently discloses that data is 'realistically mocked' and that live data requires a subscription, which is a critical behavioral trait. It also lists return fields and notes that the interface mirrors production, going beyond typical read-only disclosures.

  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 front-loaded with a clear one-sentence summary, followed by a well-organized 'Args' and 'Returns' structure. Every sentence adds value, and the mock-data note and field list are essential.

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

  Completeness5/5

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

  With no output schema, the description provides a complete list of return keys and a clear parameter description. It also explains the mocking limitation, leaving no critical information missing for an agent to invoke the tool correctly.

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

  Parameters5/5

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

  Schema coverage is 0%, so the description fully compensates by stating 'port_name: Port common name or UN/LOCODE', adding meaning beyond the bare string type. This gives the agent precise guidance on accepted formats.

  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 opens with a precise verb and resource: 'Get current congestion metrics for a port: vessel queue, wait times, capacity utilization, trend, and operational advisory.' This clearly differentiates it from sibling tools like get_port_weather or get_vessel_positions.

  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 retrieving congestion metrics but does not explicitly state when to use it over alternatives or provide exclusions. The mock-data note is useful but not a usage guideline. It would benefit from naming siblings, e.g., 'For weather conditions, use get_port_weather.'

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

• get_port_weatherA
  4.5/5.0
  Behavior4/5

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

  With no annotations, the description carries the full burden. It discloses the data source (Open-Meteo, free, no API key), mentions that wind speed is in knots and provides operational thresholds, and describes the return payload. This adds meaningful behavioral context beyond what the tool name alone implies.

  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 concise and well-organized: purpose, source, wind-speed advisory, args, and returns. Every sentence adds value, and the structure is easy to scan. No redundant or filler text.

  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 one parameter, no output schema, and no annotations, the description covers the essential details: input format, sources, key thresholds, and return contents. It doesn't specify timezone or update frequency, but these are not critical for a weather-forecast tool and the description is sufficiently complete for effective use.

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

  Parameters5/5

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

  Schema coverage is 0%, so the description fully compensates. It explains exactly what port_name accepts: common name or UN/LOCODE, with examples. This is precise and leaves no ambiguity for the single parameter.

  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 the tool retrieves current weather and a 24-hour forecast for a port. It uses a specific verb (get) and resource (port weather), and this is distinct from sibling tools that handle port lists, vessel positions, disruptions, and congestion.

  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 gives clear context for when this tool is useful, especially for assessing port operations based on wind speed thresholds. It doesn't explicitly mention alternatives or exclusions, but the context is clear enough. The wind speed thresholds provide actionable guidance on operational impact.

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

• list_major_portsA
  4.5/5.0
  Behavior4/5

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

  With no annotations, the description carries the burden. It discloses the return format (dict with region, port_count, ports) and the region options, but does not explicitly state whether the operation is read-only or discuss potential side effects; however, the 'list' action implies safety.

  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 well-structured with a summary line, a usage note, and clear Args/Returns sections. It is slightly verbose but each part adds value.

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

  Completeness5/5

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

  For a tool with one optional parameter and no output schema, the description covers purpose, usage, parameters, and return structure. It is complete for the tool's complexity.

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

  Parameters5/5

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

  Schema coverage is 0%, so the description compensates fully. It explains the region parameter, lists all valid values, and instructs that empty returns all ports.

  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 the tool lists major container ports with an optional region filter. It distinguishes itself from sibling tools (weather, vessel positions, etc.) by being the grounding tool for port discovery.

  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?

  It explicitly says to call this tool first when needing to know which ports are relevant to a route or region before calling other tools. This provides clear context, though it does not name specific alternatives or exclusions.

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

• search_disruption_newsA
  4.6/5.0
  Behavior5/5

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

  With no annotations, the description fully carries the burden and does so thoroughly: it discloses the NewsAPI dependency, rate limit (100 req/day), required API key, the high-signal flagging logic, and the location-filtering behavior with response fields (location_filter, filtered_out). This is rich behavioral context well beyond the raw tool name.

  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 somewhat long but front-loaded with the main purpose, followed by useful details, examples, and parameter explanations. Every section earns its place; the example query shapes are slightly repetitive but add value. It is not as tight as the two-sentence get_calls example but still well-structured.

  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?

  Despite no output schema and no annotations, the description explains the return structure (articles, flagged_high_signal, location_filter/filtered_out) and mentions rate limits. It does not discuss empty-result behavior or error cases, but for a search tool this is adequate coverage.

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

  Parameters5/5

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

  Schema coverage is 0%, but the description fully compensates by explaining both parameters: 'query' should lead with a place name (with examples), and 'days' gets a default and max value. This adds meaning the schema lacks entirely.

  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 states a specific action and resource: 'Search recent news for supply chain disruption signals.' It clearly distinguishes from sibling tools (list_major_ports, get_port_weather, get_vessel_positions, get_port_congestion) by focusing on news, not port/weather/vessel data.

  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?

  Provides concrete usage guidance: asks users to lead queries with the exact place name for location filtering to engage, and gives example query shapes. It also explains when the filter is NOT applied. It lacks explicit alternatives/exclusions, but the sibling tools are clearly different, minimizing the need for such exclusions.

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

• get_vessel_positionsA
  4.8/5.0
  Behavior5/5

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

  With no annotations, the description carries full responsibility and excels: it discloses the AISStream.io WebSocket source, the required AISSTREAM_API_KEY in .env, the ~8-second listening time, and that it returns a snapshot. These are critical operational details not visible in the schema.

  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 well-structured into source, region list, args, and returns. The region list is long but necessary for the agent to know valid inputs, and every sentence adds value with no filler.

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

  Completeness5/5

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

  The tool has no output schema, so the description must explain return values. It does so explicitly: dict with vessel_count, underway/anchored breakdown, and per-vessel details like MMSI, name, position, speed, course, and nav status. Combined with prerequisites and latency, the agent has everything needed to invoke and interpret results.

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

  Parameters5/5

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

  Schema coverage is 0%, so the description must explain parameters. It fully documents the region parameter with all valid named regions and suggests list_major_ports() for context, and it explains max_vessels with its default. This adds significant meaning beyond the bare 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 states it gets live vessel positions from AIS transponder data for a shipping region, using a specific verb and resource. This is distinct from sibling tools like get_port_congestion or get_port_weather, so no confusion arises.

  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 provides clear context for when to use the tool, tying it to route assessment and listing named regions. It also references list_major_ports() for context, but it doesn't explicitly state when not to use the tool or directly name alternatives for the same task.

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