SeatWiFi

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

The readOnlyHint and openWorldHint annotations already cover the safety and openness profile. The description adds useful behavioral context by explaining the scope ('fleet-wide') and the composition of the result ('providers, fleet summary, free status'), which goes beyond what annotations alone provide.

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 short sentences: the first conveys the core functionality, and the second gives usage guidance. No wasted words, and the key information 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 simple tool with one parameter and an effective schema description, the tool description fully covers what the agent needs to know to invoke it correctly. It explains what results to expect and when to use the tool, making it complete for its complexity level.

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% for the single parameter airline_code, including an example format. The description adds no additional parameter semantics, 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 what the tool returns: 'WiFi providers an airline uses fleet-wide, plus a fleet summary and whether WiFi is free.' It also distinguishes itself from flight-level tools by noting 'Use when the question is about the airline rather than one flight,' which separates it from get_flight_wifi.

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 guidance is provided: 'Use when the question is about the airline rather than one flight.' This tells the agent when to use this tool, but it does not name the specific alternative tool for flight-level queries, so it stops short of the most explicit form of 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?

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds behavioral context by characterizing this as a 'Shorter' lookup, implying a summary response, and enumerates the specific output fields. It does not disclose potential edge cases like availability of Starlink status on all flights, but the key behavioral distinction from the sibling tool is 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?

The description is two sentences long, front-loaded with the core purpose and fields, and ends with a practical pointer to the alternative tool. Every word earns its place; 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?

For a simple one-parameter lookup tool, the description sufficiently covers what the tool does, what it returns, and when to use a sibling tool. There is no output schema, but the description lists the output fields explicitly. It lacks details like response format or latency, but these are not critical for tool 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?

The schema describes flight_number as an IATA flight number with examples, yielding 100% schema description coverage. The tool description only references 'flight number' without adding new semantic detail beyond the schema, so the 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 the tool's function: 'Shorter WiFi lookup for a flight number' and lists the specific fields returned ('provider, confidence, airline, aircraft, and Starlink status'). It also distinguishes itself from the sibling get_wifi_facts by noting what it lacks ('date, tail number, or reasoning'), making the purpose 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 explicitly tells the agent when to use this tool versus an alternative: 'Use get_wifi_facts instead when you need the date, tail number, or reasoning.' This provides a clear decision rule, indicating to use get_flight_wifi for a quick summary and get_wifi_facts for detailed info.

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 and openWorldHint. The description adds the allowed status values, output fields, and the default behavior when omitting the parameter, which goes beyond the annotations. No contradictions detected.

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 pack the necessary information: what the tool returns, the status enum, output fields, and filter behavior. No wasted 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 read-only tool with one optional parameter and no output schema, the description covers the key output fields and statuses. It could mention the result is a list, but 'per aircraft type' implies grouping, making it sufficiently complete.

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 fully describes airline_code as an optional IATA filter. The description adds the important instruction to omit the parameter for all tracked airlines, adding meaning beyond the schema's baseline.

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 provides Starlink and satellite WiFi rollout progress per aircraft type, listing the specific statuses and metrics. It distinguishes itself from siblings by focusing on rollout status, though it does not explicitly name alternatives.

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 explicit usage context for the optional airline_code parameter: 'Omit airline_code for every tracked airline.' This tells the agent when to include versus omit the filter, but it does not compare against sibling tools.

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 and openWorldHint. The description adds that data is crowd-sourced, which implies variability and non-official status. This is useful context beyond the annotations, though it doesn't discuss 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 two sentences, front-loaded with the core function and output, then usage guidance and a constraint. Every sentence earns its place with no 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?

Even without an output schema, the description lists the return contents (download/upload Mbps, latency, per-provider breakdown) and clarifies the use case and input constraints. It is complete for a simple two-parameter 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 already documents both parameters with examples (100% coverage). The description adds the exclusive OR constraint ('not both'), which is critical and not in the schema. This adds meaningful value beyond the structured fields.

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 crowd-sourced in-flight WiFi speed reports with specific metrics (download/upload Mbps, latency, per-provider breakdown). It uses a specific verb 'get' and resource 'speed stats', and the content distinguishes it from sibling tools like get_wifi_facts or get_airline_wifi.

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?

It explicitly says 'Use for "is the WiFi fast enough" questions' and gives a parameter constraint ('Pass a flight_number or an airline_code, not both'). However, it does not explicitly mention alternatives or when not to use this tool, though the sibling context implies 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 already declare readOnlyHint=true and openWorldHint=true, covering the safety profile. The description adds useful context about the data sources (crowd-sourced reports, fleet assignment) and that it's a historical view, which goes beyond what annotations provide. No contradictions with annotations.

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 the core function and followed by a clear usage directive. Every word earns its place, with no redundant information.

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 one parameter, good annotations, and no output schema, the description effectively communicates the tool's purpose and data coverage. It doesn't need to explain return formats or pagination given the simple query nature, making it complete for the 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?

Schema coverage is 100% for the single tail_number parameter, which includes an example format. The description reinforces that it's for 'one aircraft' but adds no new syntax or semantic details beyond what the schema already provides, so baseline 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 provides 'WiFi provider history for one aircraft by tail number' with specific content ('crowd-sourced reports and fleet assignment'). This is a specific verb-resource-scope combination that distinguishes it from sibling tools like get_airline_wifi (airline-level) and get_flight_wifi (flight-level).

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 says 'Use when the exact airframe is known,' giving a clear when-to-use condition. It doesn't explicitly mention alternatives or when-not-to-use, but the condition implies other tools are for less specific 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 declare readOnlyHint=true and openWorldHint=true, so the description adds value by detailing the expected output components (provider probability, tail number, aircraft type, fleet fallback). It doesn't contradict annotations and provides useful context about the tool's predictive behavior.

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 deliver purpose, output scope, and tool preference with minimal verbosity. Front-loaded with 'Best answer', it is efficient and well-structured.

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 read-only prediction tool with two parameters and no output schema, the description lists key output fields and provides selection guidance. The term 'airline fleet fallback' could use elaboration, but overall it's adequate for invoking 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% for both parameters, so the description adds little beyond what the schema provides. It mentions flight number and date but provides no additional format or semantics beyond schema descriptions.

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: predicting WiFi provider for a flight number on a given date, including probability, tail number, aircraft type, and fallback. It uniquely frames itself as the 'best answer' for in-flight WiFi queries and distinguishes from sibling get_flight_wifi.

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 instructs to prefer this tool over get_flight_wifi, providing a direct alternative comparison. It also implies the primary use case ('will this flight have WiFi'), giving clear contextual 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 annotations already declare readOnly and openWorld hints. The description adds 'Large response' as a behavioral caveat and clarifies the return includes WiFi providers. This goes beyond annotations without contradicting them.

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: the first states purpose, the second gives a warning and directs to alternatives. No filler, concise and structured.

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, parameterless listing tool, the description covers the purpose, content, and usage caveats. The absent output schema is compensated by the description's mention of airline and provider information.

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 tool has zero parameters, so the description's job is minimal. It doesn't need to explain parameters; the schema already covers everything. Baseline of 4 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: list every tracked airline along with its WiFi providers. It explicitly differentiates itself from search_wifi and get_airline_wifi, which are for targeted lookups.

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 explicit guidance: use this tool when you want the full list, but for a known airline, use search_wifi or get_airline_wifi. This gives clear when-to-use and alternatives.

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 annotations already declare readOnlyHint=true and openWorldHint=true, covering the safety profile. The description adds a little context about the search scope but does not disclose return format, potential limitations, or behavior when no results are found. With annotations covering the main safety concerns, a 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 two sentences, front-loaded with the core action, and contains no redundant information. Every word earns its place, making it concise and structured effectively.

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 has only one parameter, annotations covering safety, and sibling tools providing alternatives, the description adequately covers purpose, usage, and exclusions. It does not describe the output format, but the lack of an output schema reduces this concern. A slight deduction for not mentioning what results look like.

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% coverage for the single 'query' parameter, including an example. The description does not add further semantic detail about the query parameter beyond what the schema already offers, 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 uses a specific verb ('search') and clearly defines the resource ('across airlines and flights'). It also distinguishes itself from sibling tools by specifying that it is for free-text search when you only have a name or partial term, making its purpose unmistakable.

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 this tool ('when you only have a name or partial term') and explicitly advises using a specific tool when you have a flight number, airline code, or tail number, pointing to alternatives without naming them but making the choice clear.

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