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 states it's an 'Add' operation, implying a write/mutation, but doesn't specify permissions needed, whether comments are editable, rate limits, or what happens on success/failure. This is inadequate for a mutation tool without annotation support.

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, efficient sentence with zero waste—it directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.

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 this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, error conditions, or behavioral nuances like comment persistence or validation rules. For a write operation in this context, more detail is needed to guide the agent effectively.

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, with clear documentation for all three parameters (seat_id, name, comment). The description adds no additional parameter semantics beyond what the schema already provides, so it meets the baseline score of 3 for high schema 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 action ('Add a comment') and the target resource ('to a seat'), which is specific and unambiguous. However, it doesn't differentiate from sibling tools like 'get_seat_comments' or 'delete_comment', which would require mentioning it's a write operation for creating new comments.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid seat_id), exclusions, or relationships to sibling tools like 'delete_comment' or 'get_seat_comments', leaving the agent to infer usage from context alone.

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 full burden for behavioral disclosure. 'Cancel' implies a destructive mutation, but the description doesn't address whether this requires specific permissions, if the action is reversible, what happens to associated data, or what the response looks like. It lacks crucial context for a mutation tool.

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, efficient sentence with zero wasted words. It's front-loaded with the core action and immediately specifies the key constraint ('by ID'). Every word earns its place in this minimal but complete 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?

For a destructive mutation tool with no annotations and no output schema, the description is inadequate. It doesn't explain what 'cancel' means operationally, what the expected outcome is, error conditions, or side effects. Given the complexity of reservation systems, more behavioral context is needed.

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 input schema already fully documents the single 'reservation_id' parameter. The description adds no additional semantic context beyond what's in the schema, such as format examples or validation rules. Baseline 3 is appropriate when schema does the heavy lifting.

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 action ('Cancel') and target resource ('a reservation by ID'), making the purpose immediately understandable. It doesn't differentiate from sibling tools like 'update_reservation' or 'delete_comment', but the verb+resource combination is specific enough for basic understanding.

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 no guidance on when to use this tool versus alternatives like 'update_reservation' (which might have a status field) or other cancellation methods. It mentions the 'by ID' requirement but doesn't specify prerequisites, error conditions, or contextual constraints.

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 full burden for behavioral disclosure. 'Create a new seat reservation' implies a write/mutation operation but doesn't address permissions needed, whether reservations can overlap, what happens on conflicts, or what the response looks like. For a mutation tool with zero annotation coverage, this leaves significant behavioral questions unanswered.

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, efficient sentence that communicates the core purpose without any wasted words. It's appropriately sized for a straightforward creation operation and gets directly to the point.

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 mutation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what happens after creation (e.g., returns a confirmation, reservation ID, or error), nor does it address behavioral aspects like validation rules, conflict handling, or permission requirements that would help an agent use it 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 description coverage is 100%, so the schema already documents all 4 parameters thoroughly. The description adds no additional parameter information beyond what's in the schema, which meets the baseline expectation when schema coverage is complete.

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 action ('Create') and resource ('new seat reservation'), making the purpose immediately understandable. It doesn't distinguish from sibling tools like 'update_reservation' or 'cancel_reservation', which would require explicit differentiation for a score of 5.

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 no guidance on when to use this tool versus alternatives like 'update_reservation' or 'cancel_reservation'. There's no mention of prerequisites, constraints, or appropriate contexts for creating a reservation versus other reservation-related operations.

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 states the action ('Delete') but doesn't explain if this is permanent, requires specific permissions, has side effects (e.g., affecting related data), or returns any confirmation. This is inadequate for a destructive operation.

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, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it highly concise and well-structured for quick understanding.

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 destructive nature, lack of annotations, and no output schema, the description is incomplete. It fails to address critical aspects like behavioral traits (e.g., irreversibility), usage context, or return values, leaving significant gaps for an AI agent.

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 description coverage is 100%, with the parameter 'comment_id' fully documented in the schema. The description doesn't add any meaning beyond what the schema provides (e.g., format or constraints), so it meets the baseline for high schema 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 verb ('Delete') and resource ('a comment by ID'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'get_all_comments' or 'get_seat_comments' beyond the obvious destructive nature, which prevents a perfect 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?

The description provides no guidance on when to use this tool versus alternatives. For example, it doesn't mention prerequisites (e.g., needing the comment ID from other tools) or exclusions (e.g., not for bulk deletion), leaving usage context unclear.

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 of behavioral disclosure. It only states the basic action ('Find') without detailing aspects like whether it returns a single seat or multiple matches, error handling for invalid inputs, authentication requirements, or rate limits. This leaves significant gaps in understanding the tool's 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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it easy to parse quickly.

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 lack of annotations and output schema, the description is incomplete. It does not explain what the tool returns (e.g., seat details, error messages) or address behavioral aspects like idempotency or side effects. For a tool with two required parameters and no structured output, more context is needed to guide effective use.

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 description coverage is 100%, with clear descriptions for both parameters ('office_id' and 'seat_number'). The description does not add any semantic details beyond what the schema provides, such as examples of valid seat numbers beyond 'A1' or 'B2', so it meets the baseline for adequate but unenhanced 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 clearly states the action ('Find') and resource ('a seat by seat number in an office'), making the purpose immediately understandable. However, it does not explicitly differentiate this tool from sibling tools like 'get_office_seats' or 'get_available_seats', which might also retrieve seat information, so it falls short of a perfect 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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention sibling tools such as 'get_office_seats' (which might list all seats) or 'get_available_seats' (which might filter by availability), leaving the agent without context for tool selection.

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 full burden for behavioral disclosure. It states what the tool does but reveals nothing about permissions needed, rate limits, pagination behavior, return format, or whether this might be a heavy operation. 'Get all comments' implies a read operation, but without annotations, the description should provide more context about what 'all' entails.

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, efficient sentence with zero wasted words. It's front-loaded with the core purpose and contains no redundant information. This is an excellent example of conciseness for a simple tool.

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 this is a data retrieval tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what format the comments will be returned in, whether there are access restrictions, or how 'all comments across all seats' might be paginated or limited. For a tool that presumably returns potentially large datasets, more behavioral context is needed.

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 with 100% schema description coverage, so the schema already fully documents the parameter situation. The description appropriately doesn't discuss parameters since none exist, earning a baseline 4 for not creating confusion about non-existent parameters.

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 action ('Get') and target resource ('all comments across all seats'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'get_seat_comments' or 'get_comment_counts', but the scope ('across all seats') provides some implicit distinction.

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 no guidance on when to use this tool versus alternatives like 'get_seat_comments' (for comments on a specific seat) or 'get_comment_counts' (for aggregated counts). There's no mention of prerequisites, performance considerations, or typical use cases.

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 of behavioral disclosure. It states the tool retrieves available seats but doesn't explain what 'available' means (e.g., unreserved, operational), how results are returned (e.g., list, count), or any constraints like rate limits or authentication needs. This leaves significant gaps for a tool with no annotation coverage.

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, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to understand at a glance.

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 annotations and no output schema, the description is incomplete. It doesn't explain what 'available seats' entails (e.g., definitions, return format), behavioral traits, or usage context. For a tool with three parameters and no structured output information, this leaves too many gaps for effective agent use.

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, clearly documenting all three parameters (office_id, start_date, end_date). The description adds minimal value beyond the schema, only implying a date range without providing additional context like format details or usage examples. This meets the baseline for high schema 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 with a specific verb ('Get') and resource ('available seats'), and specifies a scope ('for a specific period'). However, it doesn't differentiate from sibling tools like 'get_office_seats' or 'find_seat_by_number', which might have overlapping functionality.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, exclusions, or compare it to sibling tools like 'get_office_seats' or 'get_reservations', which could be relevant for seat availability 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states what the tool does ('Get comment count'), without explaining how it behaves—e.g., whether it returns raw counts, formatted data, error handling, or performance characteristics. For a tool with zero annotation coverage, this is insufficient.

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, efficient sentence ('Get comment count for each seat') that directly states the purpose without unnecessary words. It's front-loaded and appropriately sized for a simple tool, though it could be slightly more specific to improve clarity.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what the return value looks like (e.g., a list, a map, or aggregated total), how counts are structured, or any limitations. For a tool with no structured data to rely on, more context is needed to guide effective use.

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 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to compensate for any gaps, and it appropriately doesn't mention parameters. A baseline of 4 is applied since no parameter information is required.

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 the tool's purpose ('Get comment count for each seat'), which is a clear verb+resource combination. However, it doesn't differentiate from sibling tools like 'get_all_comments' or 'get_seat_comments', leaving ambiguity about scope and granularity. The purpose is understandable but lacks specificity about what exactly is being counted.

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 no guidance on when to use this tool versus alternatives. With siblings like 'get_all_comments' and 'get_seat_comments', it's unclear whether this tool aggregates counts across all seats, provides per-seat breakdowns, or serves a different purpose. No context, exclusions, or prerequisites 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?

No annotations are provided, so the description carries the full burden. It states 'Get' but doesn't clarify if this is a read-only operation, what permissions are required, or what happens on errors (e.g., invalid ID). For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy to parse quickly.

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 annotations, no output schema, and a simple parameter, the description is minimal. It lacks details on return values, error handling, or behavioral traits, making it incomplete for effective tool selection and invocation by an AI agent.

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%, with the parameter 'office_id' documented as 'The ID of the office'. The description adds no additional meaning beyond this, such as format examples or constraints, so it meets the baseline for high schema coverage without compensating further.

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 verb ('Get') and resource ('specific office by ID'), making the purpose understandable. However, it doesn't distinguish this tool from its sibling 'get_offices' (plural), which appears to fetch multiple offices, leaving some ambiguity about when to use each.

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 no guidance on when to use this tool versus alternatives like 'get_offices' or other sibling tools. It lacks context about prerequisites, such as needing an office ID, and doesn't mention any exclusions or specific scenarios for its use.

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 full burden. 'Get all offices' implies a read-only operation, but it lacks details on permissions, rate limits, pagination, or return format. It doesn't disclose behavioral traits beyond the basic action, 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 extremely concise at three words, front-loaded with the core action. Every word earns its place, with no wasted text, making it efficient for quick understanding.

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 annotations, no output schema, and a simple tool with 0 parameters, the description is incomplete. It doesn't explain what 'offices' are, the return format, or how it differs from siblings, leaving the agent with insufficient context for effective use.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add param info, but with no params, a baseline of 4 is appropriate as there's nothing to compensate for.

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 'Get all offices' clearly states the action (get) and resource (offices), but it's vague about scope and format. It doesn't distinguish from sibling tools like 'get_office' (singular) or 'get_office_seats', leaving ambiguity about what 'all' entails.

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 provided on when to use this tool versus alternatives. With siblings like 'get_office' (likely for a single office) and 'get_office_seats', the description doesn't clarify if this is for listing offices, fetching details, or other purposes, offering no usage 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 full burden for behavioral disclosure. While 'Get' implies a read operation, it doesn't specify whether this returns all seats regardless of availability, includes metadata, or has any rate limits or authentication requirements. The description lacks crucial behavioral context for a tool with no annotation coverage.

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, efficient sentence that communicates the core purpose without any wasted words. It's appropriately sized for a simple retrieval tool and front-loads the essential 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 read operation with one parameter and no output schema, the description is minimally adequate but lacks important context. Without annotations or output schema, it should ideally specify what 'seats' information is returned (e.g., all seats vs available seats, seat details included) to be more 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 100%, so the schema already fully documents the single 'office_id' parameter. The description adds no additional parameter information beyond what's in the schema, maintaining the baseline score for high schema 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 action ('Get') and resource ('seats for a specific office'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_available_seats' or 'find_seat_by_number', which would require more specific scope information.

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 no guidance on when to use this tool versus alternatives like 'get_available_seats' or 'find_seat_by_number'. There's no mention of prerequisites, exclusions, or appropriate contexts for selecting this specific tool.

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 states the tool retrieves a reservation by ID, implying a read-only operation, but doesn't cover aspects like error handling (e.g., what happens if the ID is invalid), authentication needs, rate limits, or response format, which are critical for a tool with no structured safety hints.

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 extremely concise and front-loaded with a single sentence: 'Get specific reservation by ID'. It wastes no words and directly communicates the core function, making it efficient and easy to parse.

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 complexity of a retrieval tool with no annotations and no output schema, the description is incomplete. It doesn't explain what data is returned (e.g., reservation details), potential errors, or how it differs from similar tools like 'get_reservations', leaving gaps in understanding the tool's full context and 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?

The input schema has 100% description coverage, with the parameter 'reservation_id' documented as 'The ID of the reservation'. The description adds no additional meaning beyond this, such as ID format or examples, so it meets the baseline of 3 where the schema does the heavy lifting without extra value from the description.

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: 'Get specific reservation by ID' specifies the verb ('Get') and resource ('reservation'), making it unambiguous. However, it doesn't distinguish itself from sibling tools like 'get_reservations' (plural), which might retrieve multiple reservations, leaving some ambiguity about sibling differentiation.

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 no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_reservations' for listing multiple reservations or 'update_reservation' for modifying one, nor does it specify prerequisites or exclusions, leaving usage context implied but not explicit.

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 of behavioral disclosure. It states it's a read operation ('Get') but doesn't mention whether it returns all reservations by default, how results are ordered, pagination behavior, error conditions, or authentication requirements. For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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 extremely concise with a single sentence that front-loads the core purpose. Every word earns its place, with no wasted verbiage or redundancy. It's appropriately sized for a simple retrieval tool.

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 moderate complexity (filtered list operation), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., list of reservation objects, error formats), behavioral details, or usage context. For a tool with 2 parameters and no structured safety hints, more guidance is needed.

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%, with both parameters ('start_date' and 'end_date') fully documented in the schema. The description adds minimal value by mentioning 'optional date filtering', which is already implied by the schema. Baseline 3 is appropriate since the schema does the heavy lifting, though the description doesn't provide additional context like date range inclusivity or default behavior.

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 verb ('Get') and resource ('reservations') with the specific capability of 'optional date filtering'. It distinguishes from siblings like 'get_reservation' (singular) and 'create_reservation' by focusing on retrieval with filtering, though it doesn't explicitly differentiate from other list-style tools like 'get_available_seats'.

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 no guidance on when to use this tool versus alternatives. It doesn't mention when to use 'get_reservation' (singular) for a specific reservation, 'get_available_seats' for availability checks, or other siblings. There's no context about prerequisites, exclusions, or typical use cases.

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 full burden for behavioral disclosure but offers minimal information. It doesn't specify whether this is a read-only operation, what format comments are returned in, if there are rate limits, or authentication requirements. 'Get' implies retrieval but lacks operational 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 extremely concise at just 5 words, with zero wasted language. It's front-loaded with the core purpose and contains no unnecessary elaboration, making it efficient for quick understanding.

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 no annotations and no output schema, the description is insufficiently complete. It doesn't explain what 'comments' are in this context, what data structure they're returned in, or any behavioral aspects like error conditions. The minimal description leaves too many operational questions unanswered.

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 mentions 'specific seat' which aligns with the 'seat_id' parameter, but adds no semantic detail beyond what the schema already provides (100% coverage). The schema fully documents the parameter as 'ID of the seat', so the description doesn't enhance understanding of parameter meaning or usage.

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 action ('Get comments') and resource ('for a specific seat'), making the purpose immediately understandable. It distinguishes from siblings like 'get_all_comments' by specifying 'specific seat', but doesn't explicitly contrast with other comment-related tools like 'delete_comment' or 'get_comment_counts'.

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 no guidance on when to use this tool versus alternatives. It doesn't mention when to choose 'get_seat_comments' over 'get_all_comments' or 'get_comment_counts', nor does it indicate prerequisites like needing a valid seat ID or appropriate permissions.

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 full burden but only states the basic action ('update an existing reservation'). It doesn't disclose behavioral traits like whether updates are reversible, what permissions are required, how conflicts with other reservations are handled, or what happens if dates overlap. For a mutation tool with zero annotation coverage, this is insufficient.

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, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a tool with good schema documentation and gets straight to the point.

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 mutation tool with no annotations and no output schema, the description is inadequate. It doesn't explain what happens on success/failure, what values are returned, or important behavioral constraints. Given the complexity of updating reservations (which involves date validation, seat availability, etc.), more context is needed.

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%, with all four parameters clearly documented in the schema itself. The description adds no additional parameter semantics beyond what's already in the schema (e.g., doesn't explain relationships between parameters or validation rules). Baseline 3 is appropriate when the schema does the heavy lifting.

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 verb ('update') and resource ('existing reservation'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'cancel_reservation' or specify what aspects can be updated beyond what's implied by the parameters.

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 no guidance on when to use this tool versus alternatives like 'cancel_reservation' or 'create_reservation'. There's no mention of prerequisites (e.g., needing an existing reservation ID) or contextual constraints (e.g., cannot update past reservations).

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