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

With no annotations, the description carries the behavioral disclosure burden. It does well by enumerating the possible status values (AVAILABLE / RAC / WL / REGRET) and qualifying the confirmation estimate with 'where known'. This gives an agent realistic expectations about output and uncertainty, though it does not cover rate limits or error 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?

The description is two sentences with no padding. The primary scope is front-loaded, and the output contract is communicated compactly. Every sentence adds value.

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 no output schema, the description adequately explains the return value (status string plus confirmation estimate). The schema covers all parameters, so an agent can call the tool correctly. A minor gap is that the format of the 'confirmation estimate' is not described, but this does not block selection or 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 input schema has 100% description coverage, so the description does not need to repeat parameter details. The prose adds minor context by grouping train, class, and quota as the core selection criteria, but it does not add semantic meaning beyond what the schema already provides.

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 specifies the resource (seat/berth availability), the scope (one train, class, quota, and date), and the key output (status string and confirmation estimate). This distinguishes it from sibling tools like get_fare, get_pnr_status, and find_trains_between_stations even without naming them.

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 scope wording implies that this tool is for checking availability on a specific already-identified train, rather than for searching trains or faresable. However, it does not explicitly state when to use it instead of siblings, nor does it mention any exclusions or alternative 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?

No annotations are provided, so the description carries the behavioral transparency burden. It does well by disclosing that only direct trains are listed, what output fields are included, and that station names are resolved automatically. It does not cover error/no-result behavior or limits, but for a read-only query tool this is adequate.

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 short, front-loaded sentences with no filler. Every sentence contributes meaningful information: the first defines the primary behavior and output, the second clarifies station input handling.

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?

There is no output schema, so the description compensates by listing key return fields: departure, arrival, duration, and available classes. It also clarifies station input behavior. An explicit pointer to plan_journey for multi-leg trips would improve completeness, but the core details are present.

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 already describes all six parameters with 100% coverage, including formats, defaults, and enums. The description only adds the station-name resolution behavior, which is already reflected in the schema. 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 states a specific action and resource: 'List direct trains connecting two stations on a given date, with departure, arrival, duration and available classes.' The phrase 'direct trains' helps distinguish it from sibling tools like plan_journey, which likely covers multi-leg routes.

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 the tool: when a user wants direct trains between two stations on a specific date. However, it does not explicitly mention alternatives or explain when to prefer plan_journey, get_train_schedule, or check_seat_availability instead.

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?

No annotations are provided, so the description carries the full burden. It usefully discloses that the result is itemized into base fare, reservation/superfast charges, catering, dynamic surcharge, and GST. However, it does not mention absence of side effects, possible errors, or behavior around unavailable fares; the read-only nature is only implied by the name.

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 with no filler. The core object appears immediately, and the enumeration of fare components adds useful detail without 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 read-only fare query with 8 parameters but no output schema, the description and schema together are largely sufficient. It explains what the returned fare will include, while optional defaults and parameter enums are already in the schema. The main gap is not explicitly routing to/from sibling tools or describing error behavior.

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 baseline is 3. The description paraphrases key dimensions like train, class, quota, and stations, but adds no extra meaning beyond what the schema already documents for each parameter.

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 resource is produced: an itemized fare for a specific train, class, quota, and station pair. It is distinguishable from siblings like get_pnr_status and check_seat_availability because it focuses on fare breakdown, not status or availability. It lacks an explicit verb, but "Itemised fare" is still a clear and specific object.

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 context is clear: use this when you need the fare for a train, class, quota, and stations. The description does not explicitly name alternatives or say when not to use it, but the distinction from seat availability and PNR status tools is reasonably evident from the domain.

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 reveals what information is returned and the status codes, which is helpful. However, it does not explicitly state that this is a read-only lookup, what happens for invalid/unknown PNRs, or whether the data reflects a point-in-time snapshot.

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?

One focused sentence that front-loads the purpose and then uses a compact list to enumerate the response contents. 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 single-parameter lookup, the description supplies enough context to invoke it: it states the input and the key output components. It is slightly incomplete because there is no output schema and no mention of invalid-PNR behavior or response envelope, but the listed fields largely compensate.

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 the single pnr parameter at 100% coverage, so the baseline is 3. The description mostly restates the '10 digit' nature and adds no format details or edge-case handling beyond the schema. Minor inconsistency: description says 10 digits while schema maxLength allows 13.

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?

Clearly identifies the operation as retrieving current PNR status and enumerates the returned details (train, date, route, class, per-passenger booking/current status, coach/berth). This is distinct from sibling tools focused on station search, schedules, fares, and availability.

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 on when to use this vs alternatives, no prerequisites, exclusions, or typical scenario. The intended use must be inferred from the tool name and the PNR parameter; nothing in the text says 'use this when the user has a PNR to check' or contrasts with 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?

With no annotations provided, the description must carry the burden of behavioral disclosure. It does add value by detailing the output content (arrival, departure, halt, etc.) and implying a read-only operation. However, it does not disclose error handling for invalid train numbers, response format, or any rate/access limitations, leaving gaps for an agent.

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 leads with the primary purpose and then lists the specific return fields. There is no fluff or redundant wording, and every phrase contributes to understanding the tool's output.

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 tool with only one parameter, no annotations, and no output schema, the description covers the essential return details (schedule fields and running days) sufficiently for a basic schedule lookup. It is not fully complete because it omits error behavior and edge cases, but the low complexity means the description is mostly adequate.

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 already provides full coverage for trainNumber with type, length constraints, and an example ('12951'). The description merely refers to 'a train number' and adds no deeper meaning about parameter format, allowed values, or how the parameter affects the result, so it stays at the schema-coverage baseline of 3.

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 a 'Full stop-by-step schedule for a train number' and lists the specific fields (arrival, departure, halt, distance, day, platform, days of week). This makes the purpose obvious and implicitly distinguishes it from siblings like find_trains_between_stations, but it does not explicitly name an alternative or specify what it is not.

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 about when to use this tool versus siblings such as plan_journey, find_trains_between_stations, or check_seat_availability. The description only states what the tool returns, without any context on preferred use cases, prerequisites, or 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?

No annotations are provided, so the description carries the burden. 'Reference list' implies a read-only, static data retrieval, which is a useful behavioral hint, but the description does not explicitly state that it makes no modifications, returns cached data, or any other behavioral characteristics. It adds 'for interpreting or constructing other tool calls' as context, but is not fully transparent about side effects.

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 clear sentence that front-loads the resource type and purpose. It contains no redundant words, but could have been slightly more direct (e.g., 'Lists...' rather than 'Reference list...'). Overall 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 simple tool with one optional parameter, full schema coverage, and no output schema, the description adequately covers what the tool provides. It does not describe the return value structure, but this is not required given the simplicity and the fact that no output schema exists.

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 has 100% description coverage for the single 'kind' parameter, including its enum values. The description itself adds no parameter-specific information, but per the baseline rule, when schema coverage is high the description need not repeat parameter details.

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 tool as a reference list for Indian Railways travel class codes and booking quota codes, with a stated purpose of interpreting or constructing other tool calls. It is specific about the resource and distinct from the operational siblings like check_seat_availability or get_fare, though it does not explicitly name them.

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 usage: 'for interpreting or constructing other tool calls', which tells the agent when this reference data is needed. However, it does not explicitly contrast with sibling tools or give conditions for when not to use it, leaving the guidance largely implicit.

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 behavioral burden. It clearly discloses the multi-step orchestration: finding trains, checking availability and fares for preferred classes, and ranking options. It does not mention failure modes, execution time, or the fact that it does not create bookings, but the core behavior is transparent.

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 waste: the first defines what the tool does, and the second gives clear usage guidance. The key information is front-loaded, and every sentence 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 description is adequate for a high-level one-shot planner: it explains purpose, main inputs, and ranking behavior, while the schema covers all 8 parameters in detail. However, with no output schema and no description of the returned ranked options, error cases, or edge conditions, it has clear gaps that could affect an agent's confidence in interpreting results.

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 parameters, defaults, constraints, and enums. The description adds only marginal conceptual context, such as 'preferred classes' and 'ranks the options', but does not need to compensate for missing parameter documentation.

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 and resource: it is a one-shot journey planner that finds trains, checks availability and fares, and ranks options. It also distinguishes itself from sibling tools by explicitly saying it replaces chaining the individual tools, so an agent can clearly tell it apart.

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: 'Use this instead of chaining the individual tools when the user asks how to get from A to B.' This clearly communicates the condition and points to the alternative approach, leaving no ambiguity about when the tool is appropriate.

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 burden. 'Find' implies a read-only lookup, but it does not explicitly state non-destructiveness, response format, or rate limits. Adequate but minimal disclosure beyond the obvious read 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?

Two sentences, zero waste. The primary purpose is front-loaded, followed immediately by a key usage directive. Every word contributes.

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 2-parameter search tool with no output schema, the description covers purpose and usage. It also implicitly promises that results include codes, which is essential for downstream tools. Minor gaps (e.g., no note on pagination or response shape) are acceptable given the tool's simplicity.

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 schema already documents both parameters. The description adds 'by name or code,' which aligns with the schema's query description but does not add significant new meaning.

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 a specific verb and resource: 'Find Indian Railways stations by name or code.' It further differentiates from sibling tools by noting that most other tools require codes, making it clear this is the lookup/conversion tool.

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 context: 'Use this first when the user names a city rather than a station code, since most other tools need codes.' It gives a clear when-to-use condition and implies the alternative (other tools need codes), though it does not name specific siblings.

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