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

With no annotations, the description carries the full burden of behavioral disclosure. It clearly conveys that this is an introspection/status tool covering three specific facts, which implies a read-only nature. However, it does not state whether authentication is required, whether it calls external systems, or any side effects. It adds useful context but omits behavioral details.

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 and wastes no words, front-loading the main point about data source configuration. The phrasing is slightly awkward ("what to set up" is a bit unclear), but the overall length and structure are appropriate for the tool's simplicity.

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 zero parameters, an output schema, and low complexity, the description covers the essential purpose well: it names the three kinds of information the tool provides. It does not need to explain return values because an output schema exists. The only missing element is a brief note on when the status should be checked, which is a usage-guidance gap rather than a completeness failure.

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 and the schema coverage is 100%, so there is nothing for the description to add on parameter meaning. Per the baseline for a parameterless tool, this scores a 4. The description correctly avoids inventing parameters that do not 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 states what the tool reports: configured data sources, timetable freshness, and setup instructions. While the verb is implicit rather than explicit ("get" or "show" is missing), the resource and scope are specific enough to distinguish it from the travel-data siblings. It could be stronger with an explicit verb, but it is not vague or tautological.

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 no guidance about when to use this tool versus alternatives. The sibling tools are clearly about live travel data, so context implies that data_status is for configuration and health checks, but no when-to-use or when-not-to-use conditions are stated. An agent must infer the use case without explicit direction.

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 explains the key behavioral nuance: before the live platform is announced, the booked timetable platform is returned and flagged as 'booked'. This is valuable context beyond a simple 'get platform' statement.

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 brief and front-loads the core purpose, followed by an important timing caveat. It is slightly awkwardly phrased ('Which platform one train leaves from') but remains efficient and free of unnecessary filler.

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 the parameter schema is fully described, the description covers the essential behavioral context. It explains the live-versus-booked distinction, which is the main nuance an agent needs. It could mention how the train is identified via station and time, but the schema already provides this.

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%, so the schema already documents all three parameters. The description does not add much parameter-level detail beyond what the schema provides, which is acceptable given the high coverage.

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: returning the platform from which a single train departs. It also distinguishes the live vs booked platform behavior, which helps differentiate it from sibling tools like platform_departures, though it does not explicitly name any sibling.

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 useful context about when live platforms become available (~10 minutes before departure) and that booked platforms are returned otherwise. However, it does not explicitly state when to use this tool versus alternatives such as platform_departures or live_departures, leaving some inference to the agent.

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, the description must carry the behavioral disclosure. It does state that results are ordered by 'best match first', which is useful, but it omits other behaviors like case sensitivity, handling of partial matches, or error conditions. For a simple lookup, this is minimal but not severely lacking.

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, front-loaded sentence that efficiently states the purpose and ordering behavior. No filler or redundant phrasing.

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's low complexity and the presence of an output schema, the description is adequate but not rich. It covers the core lookup behavior but does not mention result format, case sensitivity, or limit semantics. For a straightforward station lookup, it is minimally 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?

Schema description coverage is only 50%: the query parameter has a description, but limit has none. The tool description reiterates that query accepts name or CRS code, adding little beyond the schema. It provides no clarification for the limit parameter, leaving it underspecified.

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 looks up GB railway stations by name or CRS code and returns best match first. This specifies a verb, resource, and search criteria, but it does not explicitly differentiate from sibling tools like live_departures or plan_journey, so it misses the top score.

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?

No guidance is given on when to use this tool versus alternatives. The description implies it is for station lookup, but there is no explicit mention of when to prefer it over other tools or any exclusions.

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, the description carries the behavioral burden. It discloses a meaningful data-source precedence and that results are approximated to the next ~2 hours. This is beyond what the schema or annotations would show, though it leaves other live-data behaviors (update cadence, cancellation handling) unstated.

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 the core purpose and the data-source fallback with no filler. The main limitation is jargon ('RTT'), but the structure itself is appropriately sized 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?

The presence of an output schema excuses return-value detail, and the description covers purpose and behavior. However, it does not orient the agent relative to the sibling tools or explain the acronym, leaving moderate context gaps for a 4-parameter tool with no annotations.

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 description adds no parameter-level semantics; station, rows, from_station, and include_calling_points are left entirely to the schema. Schema description coverage is only 50%, so the description should compensate for the undocumented parameters but does not.

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 identifies the resource ('arrivals') and the time window ('next ~2 hours'), and the tool name reinforces a station-level live arrivals lookup. It stops short of a verb form and does not explicitly contrast with live_departures, so it loses a point.

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?

No when-to-use guidance is provided. The fallback chain ('Darwin's arrivals product if configured, then RTT, then booked timetable times') describes data sourcing, not when to choose this tool over live_departures, timetable, or service_details. None of the sibling tools are mentioned.

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, the description carries the transparency burden. It usefully discloses the ~2-hour window, the types of information returned, and the data-source fallback chain, which are meaningful behavioral traits beyond 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.

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

The description is compact and front-loaded: it states the core purpose first, then adds a concise data-source note. Every sentence earns its place with 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?

The description covers core behavior and data provenance, and an output schema exists, so return structure is not a gap. However, it lacks sibling differentiation and does not compensate for the undocumented parameters, making it only partially complete for a 5-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 description coverage is 60%, so the schema already explains several parameters. The description adds a time-window frame but does not clarify rows, include_calling_points, or how offset_minutes interacts with the board, leaving some parameter semantics under-specified.

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 identifies a live departure board with a specific time horizon and output content (expected times, platforms, delays, cancellations). It is distinct from live_arrivals, though it does not explicitly differentiate itself from departure_platform or platform_departures.

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?

No explicit guidance is given about when to use this tool over siblings like live_arrivals, platform_departures, or timetable. The mention of Darwin/RTT/timetable fallback provides data-source context but not usage routing.

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 behavioral burden. It discloses meaningful operational traits: results are ordered fastest-first, cross-London transfers are approximate walk/Tube links, live Darwin times are only added for today's trains within the next two hours, and at-risk connections are flagged. This goes beyond a typical terse description, though it does not address read-only/side-effect behavior explicitly.

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?

Three sentences, each earning its place: the core purpose, the output ordering and approximation caveat, and the live-data behavior. It is front-loaded with the most decision-relevant information and contains no filler or repetition.

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's complexity, the description covers the essential choices an agent must make: output ordering, change limits, cross-London transfer approximations, and live data conditions. The presence of an output schema relieves the description of explaining return fields in detail. It is slightly incomplete only in not clarifying count's meaning and not naming sibling alternatives, but it is otherwise robust.

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 75%, so most parameters are already documented. The description adds useful prose meaning for max_changes and live, but count remains undocumented in both the schema and the description, leaving its role as the number of returned journey options implicit rather than explicit. This partial compensation keeps it at the baseline rather than above it.

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: 'Plan journeys between two stations, with changes up to max_changes.' It also states the output ordering and the fewest-changes option, clearly differentiating it from sibling tools like live_departures and timetable, which cover station departures or single services rather than end-to-end journey planning.

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: use this tool when a journey between two stations is needed, including changes and cross-London transfers. It does not explicitly name alternatives or state when not to use it, so it stops short of the highest bar, but the intended use case is unmistakable.

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, the description carries the behavioral transparency burden. It usefully discloses the live-vs-booked platform matching logic and the caveat that a booked platform can change. It doesn't cover every possible behavioral aspect like authentication or error cases, but for a simple read-style query tool this is strong disclosure.

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 filler. The primary scope and time window are front-loaded, and the important matching caveat is added in the second sentence. Every part earns its place.

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 core domain nuance (platform assignment can change) is disclosed, and an output schema exists to define return values. It could be more explicit about choosing this over related sibling tools, but for a single-platform departure query it provides enough context for correct 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 already documents 'station' and 'platform' with meaningful descriptions, while 'count' has constraints but no explicit semantic description. The tool description adds no parameter-level detail beyond what the schema provides, and schema coverage is moderate at 67%, so this is adequate but not enriched.

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 resource ('one platform') and behavior ('next trains leaving') with a clear time horizon ('next ~2 hours'). This distinguishes it from sibling tools like live_departures, which imply station-wide departures, and departure_platform, which focuses on determining a train's platform.

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 clearly implies usage: use this when you need departures from a specific platform within about two hours. However, it does not explicitly state when not to use it or name alternatives such as live_departures or departure_platform, so the guidance is implied rather than prescribed.

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, the description carries the full burden of behavioral disclosure. It does disclose the key caveat that live times are only provided 'where available' and implies a read-only lookup. However, it does not address failure behavior, data source freshness, or whether historical services are supported; the output schema covers return structure.

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 with the core purpose front-loaded and the live-times caveat appended. Every word earns its place, and there is no redundant or filler 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?

For a one-parameter read tool with an output schema, the description plus schema is largely sufficient for an agent to call it correctly. The only notable gap is the lack of explicit usage guidance relative to sibling tools, but that is already captured in the usage_guidelines dimension.

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 the parameter description already explains the accepted service_id formats. The tool description adds no new parameter-level meaning beyond implying the ID identifies a train service, 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 identifies the resource ('one train') and the content ('all stops'), and the 'live times where available' qualifier distinguishes it from a static timetable. It lacks an explicit verb, but the intent is unambiguous and it is easily differentiated from siblings like live_departures and timetable.

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 phrase 'for one train' implies when to use this tool, but there is no explicit guidance on when to prefer it over alternatives such as timetable or live_departures. No exclusions or alternative tool names are mentioned, leaving the agent to infer the appropriate 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?

With no annotations provided, the description carries the full burden, and it does add meaningful context: 'booked' signals this is the planned timetable rather than real-time, and the horizon ('usually months ahead') is disclosed. However, it does not say how out-of-coverage dates are handled, whether live disruption is reflected, or what the response shape implies, so the behavioral disclosure remains partial.

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 with zero filler. Purpose and scope are front-loaded first, and the usage caveat follows immediately; every word earns its place.

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?

An output schema exists, so return values need no explanation. The description handles the primary use case well, but for a 9-parameter tool it leaves unaddressed the arrivals board, row/window controls, and calling-point behavior, relying on the schema to carry those details.

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 56%, so the description is expected to partially compensate. It reinforces the two core parameters ('at a station' for station, 'any date the timetable covers' for date) and adds the horizon semantics. But rows, window_minutes, include_calling_points, and board have no schema descriptions and the description offers nothing for them, so the gap persists.

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 ('Booked train times at a station') and clarifies the temporal scope ('any date the timetable covers, usually months ahead'). It explicitly differentiates from the closest sibling by pointing to live_departures for real-time queries, so an agent can tell them apart without opening schemas.

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 when-to-use guidance ('for future trips') and an explicit when-not-to with a named alternative ('for right now prefer live_departures'). It does not, however, address other overlapping siblings such as live_arrivals (given the board=arrivals option) or plan_journey, leaving some routing to inference.

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