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 mentions 'Google Meet conference and guest permissions', which hints at behavioral aspects like conference creation and permission settings. However, it lacks details on critical behaviors: whether this requires authentication, what happens on failure, if it's idempotent, or the response format. 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 front-loads the core purpose ('Create a new calendar event') and adds qualifying details ('with Google Meet conference and guest permissions'). There's no wasted verbiage, and it's appropriately sized for the tool's complexity.

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 (12 parameters, mutation operation) and lack of annotations and output schema, the description is incomplete. It doesn't cover behavioral traits like error handling, authentication needs, or return values, which are crucial for an agent to use this tool effectively. The description alone is inadequate for safe and correct 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?

Schema description coverage is 100%, so the schema fully documents all 12 parameters. The description adds minimal value beyond the schema by implying that parameters relate to 'Google Meet conference and guest permissions', but it doesn't explain parameter interactions or provide additional context. 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 specific action ('Create a new calendar event') and distinguishes it from siblings by specifying 'with Google Meet conference and guest permissions'. It uses a precise verb ('Create') and identifies the resource ('calendar event'), making the purpose unambiguous and differentiated from other tools like calendar_v3_update_event or calendar_v3_delete_event.

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 context by mentioning 'Google Meet conference and guest permissions', suggesting this tool is for creating events with those features. However, it doesn't explicitly state when to use this vs. alternatives like calendar_v3_quick_add (for simpler events) or calendar_v3_update_event (for modifications). The guidance is present but not comprehensive.

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 deletes an event, implying a destructive mutation, but fails to mention critical aspects like permissions required, whether deletion is permanent or reversible, rate limits, or error handling. This leaves significant gaps for an agent to understand 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 with no wasted words. It front-loads the key information (API context and action) and is appropriately sized for a simple delete operation, 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 tool's complexity (a destructive mutation with no annotations and no output schema), the description is incomplete. It lacks details on behavioral traits (e.g., permanence, auth needs), expected outcomes, or error cases, which are crucial for safe and effective use 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?

The input schema has 100% description coverage, fully documenting both parameters (event_id and calendar_id with its default). The description adds no additional parameter information beyond what the schema 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 ('Delete') and resource ('a calendar event'), with the API version context ('Calendar API v3') providing specificity. However, it doesn't distinguish this tool from its siblings like 'calendar_v3_move_event' or 'calendar_v3_update_event' in terms of purpose, 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?

No guidance is provided on when to use this tool versus alternatives. For example, it doesn't mention prerequisites (e.g., needing an existing event ID) or compare to siblings like 'calendar_v3_move_event' for moving instead of deleting. The description lacks any context for usage decisions.

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 full burden but lacks behavioral details. It doesn't disclose whether this is a read-only operation, what permissions are required, how results are returned (e.g., format, pagination), or any rate limits. The description is minimal and doesn't compensate for the absence of annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is a single, efficient sentence with zero waste. It's front-loaded with the core purpose and uses brackets to denote API version without unnecessary elaboration, making it highly concise 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?

Given no annotations and no output schema, the description is incomplete for a tool that queries availability. It doesn't explain what the output looks like (e.g., busy slots, free times), error conditions, or behavioral traits like authentication needs. For a 3-parameter tool with full schema coverage but missing context, this is inadequate.

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 fully documents parameters (calendar_ids, time_min, time_max). The description adds no additional meaning beyond implying these are used for querying, which is already clear from the schema. Baseline 3 is appropriate as 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 action ('Query free/busy information') and resource ('for calendars'), with the API version ('Calendar API v3') providing context. It distinguishes from siblings like calendar_v3_list_events by focusing on availability rather than event details, though it doesn't explicitly name alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives is provided. The description doesn't mention prerequisites, such as needing calendar access, or compare it to siblings like calendar_v3_list_events for checking schedules. Usage is implied by the name but not explicitly stated.

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 only states the basic function ('Get details') without mentioning authentication requirements, rate limits, error responses, or what specific details are returned. For a read operation in a calendar API, this leaves significant gaps in understanding how the tool behaves in practice.

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 (one sentence) and front-loaded with the essential information. Every word serves a purpose: the API context, the action, and the resource. There's no wasted verbiage or redundant information.

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

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

For a tool with no annotations and no output schema, the description is insufficiently complete. While the purpose is clear, it doesn't explain what 'details' are returned, how authentication works, potential error cases, or performance characteristics. Given the complexity of calendar events and the lack of structured output documentation, more context would be helpful for effective tool 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, with the single parameter 'event_id' clearly documented. The description doesn't add any parameter information beyond what the schema provides, but with complete schema coverage, the baseline score of 3 is appropriate. No additional semantics about event ID format or sources are mentioned.

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 details') and resource ('specific calendar event'), making the purpose immediately understandable. However, it doesn't distinguish this tool from its sibling 'calendar_v3_list_events' which also retrieves event information, though in a different format (list vs. single item). The API version context ('Calendar API v3') is helpful but not essential for purpose clarity.

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 about when to use this tool versus alternatives. The agent must infer from the name and description that this retrieves a single event by ID, while 'calendar_v3_list_events' retrieves multiple events, but this distinction isn't explicitly stated. There's no mention of prerequisites, error conditions, 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 the full burden of behavioral disclosure. It states the action ('List all calendars') but doesn't mention permissions, rate limits, pagination, or output format. This leaves significant gaps for a tool that likely interacts with user data.

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 front-loads the key information ('List all calendars available to the user'). There's no wasted text, making it highly concise 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?

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'available to the user' means (e.g., permissions), how results are returned, or behavioral traits like pagination. For a list operation in a calendar API, this leaves critical context missing.

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 appropriately doesn't discuss parameters, earning a baseline score of 4 for not adding unnecessary information.

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 ('List') and resource ('all calendars available to the user'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'calendar_v3_list_events', which might cause confusion about scope.

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 like 'calendar_v3_list_events' or 'calendar_v3_freebusy_query'. The description lacks context about use cases, prerequisites, or exclusions, leaving the agent to infer usage.

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 mentions 'List upcoming calendar events with Google Meet conferences', which implies a read-only operation, but does not disclose behavioral traits such as pagination, rate limits, authentication needs, or what happens if no events are found. The description is minimal and lacks critical operational context.

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 front-loads the core purpose. It avoids unnecessary words, but could be slightly more structured by explicitly mentioning it's for listing events (not creating or updating). Overall, it is appropriately concise with no wasted text.

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 for a tool with 4 parameters. It lacks details on behavioral aspects (e.g., pagination, error handling), does not explain the 'Google Meet conferences' filter, and provides no guidance on usage versus siblings. For a read operation in a complex API context, this leaves significant gaps.

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 fully documents all parameters (max_results, time_min, time_max, calendar_id) with descriptions and defaults. The description does not add any additional meaning or context beyond what the schema provides, such as explaining the 'Google Meet conferences' filter or parameter interactions. Baseline 3 is appropriate as the schema handles 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 ('List') and resource ('upcoming calendar events'), and specifies 'with Google Meet conferences' to indicate a key feature. However, it does not explicitly differentiate from siblings like 'calendar_v3_get_event' (single event) or 'calendar_v3_list_calendars' (list calendars), leaving some ambiguity in scope.

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 provided on when to use this tool versus alternatives. The description mentions 'upcoming calendar events with Google Meet conferences', which implies a focus on events with conferences, but it does not state when to choose this over 'calendar_v3_list_calendars' or other event-related tools, nor does it mention 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 full burden of behavioral disclosure. It states the tool moves an event, implying a mutation operation, but doesn't disclose critical traits such as required permissions (e.g., write access to both calendars), side effects (e.g., notifications sent), error conditions (e.g., if calendars don't exist), or response format. For a mutation 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 a single, efficient sentence that front-loads the key action ('move a calendar event') and includes the API version context. There is no wasted verbiage or redundancy, 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 complexity (a mutation operation with 3 required parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects like permissions, side effects, or error handling, nor does it explain return values. For a tool that modifies data, this leaves the agent with insufficient context to use it safely and 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?

Schema description coverage is 100%, with all three parameters (event_id, source_calendar_id, destination_calendar_id) clearly documented in the input schema. The description adds no additional meaning beyond what the schema provides (e.g., no examples, format details, or constraints). According to the rules, when schema coverage is high (>80%), the baseline score is 3 even without param info in 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 action ('move') and resource ('calendar event'), specifying it's from one calendar to another. It distinguishes this tool from siblings like create_event, delete_event, or update_event by focusing on relocation rather than creation, deletion, or modification. However, it doesn't explicitly differentiate from all siblings (e.g., it's less clear how it differs from freebusy_query or quick_add in purpose).

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. The description doesn't mention prerequisites (e.g., needing permissions on both calendars), exclusions (e.g., not for recurring events), or comparisons to siblings like update_event (which might handle calendar changes differently). Usage is implied only by the action described, with no explicit context or alternatives stated.

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 this is a creation tool but doesn't mention permissions required, whether it's idempotent, error handling, or what happens on success. The description lacks crucial behavioral context for a write 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 extremely concise - just 7 words total. It's front-loaded with the core functionality and every word earns its place. The bracketed API version context is minimal and useful.

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 creation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what gets returned, error conditions, or behavioral constraints. The natural language aspect is mentioned but not elaborated (e.g., parsing limitations, supported formats).

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 both parameters. The description adds no additional parameter semantics beyond what's in the schema descriptions. The baseline of 3 is appropriate when the schema does all the work.

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: 'Create event using natural language' specifies the verb (create) and resource (event) with the unique natural language aspect. It distinguishes from sibling calendar_v3_create_event by mentioning natural language processing, though not explicitly naming the alternative.

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 context through 'using natural language' and the text parameter example, suggesting this tool is for quick, informal event creation. However, it doesn't explicitly state when to use this vs. calendar_v3_create_event or provide any exclusions or prerequisites.

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 full burden but provides minimal behavioral information. It states it's an update operation but doesn't disclose what happens with partial updates, permission requirements, whether changes are reversible, rate limits, or error conditions. This is inadequate for a mutation tool with zero 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 extremely concise - a single sentence with zero wasted words. It's front-loaded with the essential information (API version and core action) and contains no unnecessary elaboration.

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 11 parameters and no annotations or output schema, the description is insufficient. It doesn't explain what the tool returns, error handling, authentication requirements, or important behavioral aspects like partial updates. The context demands more completeness than provided.

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 11 parameters thoroughly. The description adds no additional parameter information beyond what's in the schema, maintaining 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 ('Update') and resource ('an existing calendar event'), making the purpose unambiguous. It distinguishes from creation and deletion tools by specifying 'existing', but doesn't explicitly differentiate from similar update operations like 'move_event' or 'update_space'.

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 about when to use this tool versus alternatives. The description doesn't mention prerequisites (like needing event_id), when not to use it (e.g., for creating new events), or how it differs from sibling tools like 'move_event' or 'update_space'.

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 creates a space but lacks critical details: whether this is a mutating operation (implied by 'Create'), what permissions or licenses are needed beyond the parameter hints, potential side effects (e.g., resource limits), or what the output looks like. The mention of 'advanced configuration' is vague and doesn't compensate for the missing behavioral context.

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 front-loads the key information: API version ('Meet API v2 GA'), action ('Create'), resource ('Google Meet space'), and scope ('with advanced configuration'). There's no wasted verbiage, 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 the tool's complexity (9 parameters, creation operation) and lack of annotations and output schema, the description is insufficient. It doesn't address behavioral aspects like mutation effects, error conditions, or return values, leaving significant gaps for an agent to understand how to use the tool effectively in practice.

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 each parameter well-documented (e.g., defaults, requirements like 'requires Google Workspace'). The description adds no additional parameter semantics beyond the schema, so it meets the baseline of 3 where the schema does the heavy lifting. However, it doesn't explain how parameters interact or their overall impact on the created space.

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 ('Google Meet space'), and specifies 'with advanced configuration' which hints at the tool's scope. However, it doesn't explicitly differentiate from sibling tools like 'meet_v2_update_space' or 'calendar_v3_create_event', which would require a more specific 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. It doesn't mention prerequisites (e.g., authentication requirements), compare it to other creation tools in the sibling list, or indicate scenarios where it's preferred over simpler options. This leaves 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?

No annotations are provided, so the description carries full burden. It mentions 'End the active conference,' implying a destructive action, but fails to disclose critical behavioral traits like required permissions, whether the action is reversible, effects on participants, or error conditions. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

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 front-loads the key action ('End the active conference') and includes relevant context ('Meet API v2 GA'). There is no wasted verbiage, making it appropriately sized and well-structured for quick comprehension.

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 as a destructive operation with no annotations and no output schema, the description is incomplete. It lacks details on behavioral outcomes, error handling, or return values, which are crucial for safe invocation. The high schema coverage doesn't compensate for these gaps in a mutation context.

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

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

Schema description coverage is 100%, with the parameter 'space_name' fully documented in the schema. The description adds no additional meaning beyond the schema, such as format examples or constraints. With high schema coverage, the baseline is 3, as the description doesn't compensate but also doesn't detract.

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 ('End') and target ('active conference in a Google Meet space'), specifying it's for the Meet API v2 GA. It distinguishes from siblings like meet_v2_get_conference_record or meet_v2_list_conference_records by focusing on termination rather than retrieval. However, it doesn't explicitly differentiate from other destructive tools like meet_v2_update_space, keeping it at a 4.

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, such as meet_v2_update_space for modifying a space instead of ending a conference, or prerequisites like needing an active conference. It lacks explicit when/when-not instructions or named alternatives, resulting in minimal 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 but offers minimal behavioral insight. It implies a read-only operation ('Get details') but doesn't disclose error conditions, authentication needs, rate limits, or what 'details' include (e.g., metadata, participants, recordings). For a tool with zero annotation coverage, this is inadequate transparency.

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 front-loads the core action ('Get details'). However, the inclusion of '[Meet API v2 GA]' is redundant with the tool name prefix 'meet_v2_', slightly reducing conciseness, though it doesn't significantly impact readability.

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 for a tool that retrieves data. It doesn't explain what 'details' entail (e.g., structure, fields, or links to related resources like participants), leaving the agent uncertain about the return value and overall tool behavior in context.

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

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

Schema description coverage is 100%, so the input schema fully documents the single parameter 'conference_record_name'. The description adds no additional parameter semantics beyond what's in the schema (e.g., format examples, validation rules, or how to obtain the name), resulting in a baseline score 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 verb ('Get details') and resource ('specific conference record'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'meet_v2_list_conference_records' (which lists multiple records) or 'meet_v2_get_participant' (which gets participant details), leaving some ambiguity in 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 prerequisites (e.g., needing a conference record name), contrast with list operations, or specify use cases like retrieving metadata for a known record, 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 the full burden of behavioral disclosure. It states it's a read operation ('Get details'), but doesn't cover aspects like authentication needs, rate limits, error handling, or what 'details' entail (e.g., participant metadata, status). 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 front-loads the API version and core purpose. It avoids unnecessary words, though it could be slightly more informative without sacrificing brevity, such as hinting at the type of details returned.

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 participant retrieval tool with no annotations and no output schema, the description is insufficient. It lacks details on return values, error cases, or behavioral traits, making it incomplete for effective agent use without additional context.

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

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

Schema description coverage is 100%, with the parameter 'participant_name' fully documented in the schema. The description doesn't add any additional meaning beyond what the schema provides, such as format examples or usage notes, but the high schema coverage justifies the baseline score 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 action ('Get details') and target ('a specific participant'), specifying it's for the Meet API v2 GA. However, it doesn't distinguish this tool from its sibling 'meet_v2_get_participant_session', which also retrieves participant-related data but for sessions, leaving some ambiguity in 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?

No guidance is provided on when to use this tool versus alternatives like 'meet_v2_list_participants' or 'meet_v2_get_participant_session'. The description implies usage for a specific participant but offers no context on prerequisites, error conditions, or comparative scenarios 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 carries the full burden of behavioral disclosure. It only states the action ('Get details') without mentioning permissions, rate limits, error conditions, or what the output entails. This is inadequate for a tool that likely involves data access.

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 front-loads the key information ('Get details of a specific participant session') with no wasted words. The API version note is minimal and relevant.

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 insufficient. It doesn't explain what details are returned, potential errors, or how this fits into the broader Meet API workflow, leaving significant gaps for an agent to use it 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?

Schema description coverage is 100%, so the schema fully documents the single parameter 'participant_session_name'. The description adds no additional meaning beyond what's in the schema, such as format examples or usage tips, resulting in the baseline score.

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 details') and resource ('specific participant session'), making the purpose unambiguous. However, it doesn't distinguish this tool from its sibling 'meet_v2_get_participant' or 'meet_v2_list_participant_sessions', which handle related participant data, 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 like 'meet_v2_get_participant' or 'meet_v2_list_participant_sessions'. It lacks context about prerequisites or scenarios where this specific session detail retrieval 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 provided, the description carries the full burden of behavioral disclosure. It states it 'Get details' but doesn't specify what details are returned, whether it's a read-only operation, any authentication needs, rate limits, or error conditions. This is inadequate for a tool with zero 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 with no wasted words. It front-loads the key information ('Get details of a specific recording') and includes a version note ('Meet API v2 GA') that adds context without clutter.

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 'details' are returned, the response format, or any behavioral aspects like error handling. For a tool with no structured output information, this leaves 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 input schema has 100% description coverage, fully documenting the 'recording_name' parameter. The description adds no additional parameter information beyond what the schema provides, so it meets the baseline for high schema coverage without compensating value.

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 details') and resource ('a specific recording'), making the purpose understandable. However, it doesn't distinguish this tool from sibling tools like 'meet_v2_get_conference_record' or 'meet_v2_get_transcript', which also retrieve specific Meet resources, so it lacks 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. For example, it doesn't mention when to choose this over 'meet_v2_list_recordings' for browsing or other 'get' tools for different resource types, leaving usage context implied at best.

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 for behavioral disclosure. It states it 'Get details' but doesn't specify what details are returned, error conditions, authentication needs, rate limits, or whether it's idempotent. For a read operation without annotations, this leaves significant gaps in understanding how the tool behaves.

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 front-loads key information: API version, action, and resource. There is no wasted text, and it directly communicates the tool's purpose 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?

Given no annotations and no output schema, the description is incomplete for a tool that retrieves details. It doesn't explain what 'details' include, return format, or potential errors. For a get operation in a complex API like Meet, more context is needed to understand the tool's full scope 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?

Schema description coverage is 100%, with the parameter 'space_name' fully documented in the schema. The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints. Baseline score of 3 is appropriate since the schema handles parameter documentation adequately.

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 details') and resource ('Google Meet space'), and specifies the API version ('Meet API v2 GA'). It distinguishes from siblings like meet_v2_create_space or meet_v2_update_space by focusing on retrieval rather than creation or modification. However, it doesn't explicitly differentiate from other get operations like meet_v2_get_conference_record or meet_v2_get_participant, which slightly reduces specificity.

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 an existing space), exclusions, or comparisons to siblings like meet_v2_list_conference_records for bulk retrieval. Usage is implied by the verb 'Get,' but explicit context is lacking.

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 it 'Get details' but doesn't clarify what details are returned, if it's a read-only operation, potential errors, or any rate limits. This leaves significant gaps in understanding how the tool behaves beyond its basic purpose.

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 for a simple tool, though it could be slightly more informative to improve completeness without losing conciseness.

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 transcript retrieval tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'details' include, how the transcript is formatted, or any behavioral aspects like error handling. This leaves the agent with incomplete 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 100% description coverage, with the parameter 'transcript_name' fully documented in the schema. The description doesn't add any extra meaning about parameters beyond what's in the schema, so it meets the baseline of 3 for high schema coverage without compensating value.

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 details') and resource ('a specific transcript'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'meet_v2_list_transcripts' or 'meet_v2_list_transcript_entries', which would require a more specific distinction to earn a 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?

No guidance is provided on when to use this tool versus alternatives. For example, it doesn't mention that this retrieves details for a single transcript identified by name, whereas 'meet_v2_list_transcripts' might be used to browse multiple transcripts. The description lacks any context about 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'historical meetings' which adds some context about scope, but doesn't describe pagination behavior (implied by page_size parameter), authentication requirements, rate limits, error conditions, or what constitutes a conference record. The description is too sparse for a tool that presumably returns potentially sensitive meeting data.

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 (one sentence) and front-loaded with the key information. However, it's arguably too brief given the tool's purpose - a single sentence may not provide enough context for proper usage.

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, no output schema, and parameters that imply pagination and filtering capabilities, the description is inadequate. It doesn't explain what a conference record contains, how results are structured, or provide any examples of filter usage. The mention of 'historical meetings' is helpful but insufficient for complete understanding.

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 both parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema. This 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 ('List') and resource ('conference records for historical meetings'), and the API version context is helpful. However, it doesn't explicitly differentiate from sibling tools like 'meet_v2_list_participants' or 'meet_v2_list_recordings' which also list related resources.

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 what distinguishes listing conference records from other list operations in the Meet API or when historical meetings would be relevant versus current ones.

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 mentions the API version ('Meet API v2 GA') but fails to describe key behaviors like pagination handling (implied by 'page_size'), rate limits, authentication requirements, or the format of returned data, which are critical for a list 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 that front-loads the core action ('List participants'). It includes the API version as useful context without unnecessary elaboration, though it could be slightly more structured for 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 complexity of a list operation with pagination, no annotations, and no output schema, the description is incomplete. It lacks details on return values, error handling, or behavioral constraints, leaving significant gaps for the agent to infer usage.

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 fully documents both parameters. The description adds no additional semantic context beyond what's in the schema (e.g., it doesn't clarify the structure of 'conference_record_name' or usage of 'page_size'), resulting in a baseline score.

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 ('List') and resource ('participants for a conference record'), making the purpose specific and understandable. However, it doesn't differentiate from sibling tools like 'meet_v2_list_participant_sessions' or 'meet_v2_get_participant', which would require explicit comparison to achieve 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?

No guidance is provided on when to use this tool versus alternatives. For example, it doesn't explain when to choose this over 'meet_v2_get_participant' for individual details or 'meet_v2_list_participant_sessions' for session-level data, leaving the agent without context for 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 but offers minimal behavioral insight. It doesn't disclose whether this is a read-only operation, pagination behavior (beyond the schema's page_size), rate limits, authentication needs, or what the output looks like (e.g., session details format). The description only repeats the tool's purpose without adding operational context.

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 front-loads the key information (API version, action, target) and avoids redundancy. Every part earns its place by clarifying scope and resource.

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, no output schema, and 2 parameters, the description is incomplete. It lacks behavioral details (e.g., read-only nature, pagination), output expectations, and usage guidelines. While the schema covers parameters well, the overall context for an AI agent to correctly invoke this tool is insufficient.

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 fully documents both parameters (participant_name format, page_size defaults/limits). The description adds no additional parameter semantics beyond what's in the schema, such as examples or edge cases. Baseline 3 is appropriate when the schema does all the work.

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 ('List sessions') and target resource ('for a specific participant'), with the API version context ('Meet API v2 GA'). It distinguishes from sibling tools like 'meet_v2_list_participants' by focusing on sessions rather than participants themselves. However, it doesn't explicitly differentiate from 'meet_v2_get_participant_session' (singular vs. plural).

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. The description doesn't mention prerequisites (e.g., needing a valid participant identifier), exclusions, or comparisons to sibling tools like 'meet_v2_get_participant_session' (single session) or 'meet_v2_list_participants' (list participants). Usage context is implied but not stated.

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. It mentions listing recordings but doesn't disclose behavioral traits like pagination, rate limits, authentication needs, error conditions, or what the output includes (e.g., format, metadata). For a list operation with zero annotation coverage, this is a significant gap in transparency.

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 front-loads the API version and core purpose ('List recordings for a conference record'), making it easy to scan. Every word earns its place 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?

Given no annotations and no output schema, the description is incomplete for a list tool. It lacks details on behavior (e.g., pagination, sorting), output format, error handling, and dependencies. While concise, it doesn't provide enough context for an agent to use it effectively beyond the basic parameter.

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 single parameter 'conference_record_name' fully documented in the schema. The description adds no additional meaning beyond implying the parameter is required for the listing. Baseline 3 is appropriate as the schema does the heavy lifting, but no extra context (e.g., how to obtain the name) is provided.

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 ('List recordings') and the target resource ('for a conference record'), with the API version context ('Meet API v2 GA'). It distinguishes from siblings like meet_v2_get_recording (singular) and meet_v2_list_transcripts (different resource). However, it doesn't explicitly differentiate from other list operations like meet_v2_list_participants, though the resource specificity helps.

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 on when to use this tool versus alternatives is provided. The description doesn't mention prerequisites (e.g., needing a conference record from meet_v2_list_conference_records first), exclusions, or comparisons to other list tools. It assumes context but offers no explicit usage instructions.

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 mentions the API version ('v2 GA') and that entries are 'individual speech segments', but doesn't describe pagination behavior (despite having a page_size parameter), rate limits, authentication requirements, error conditions, or what the output looks like. For a listing tool with no annotation coverage, this leaves significant 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 front-loads key information (API version, action, resource). The bracketed API version note is slightly distracting but not wasteful. Every element serves a purpose, though it could be slightly more polished.

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 listing operation with pagination behavior implied by the page_size parameter, the description is incomplete. It doesn't explain what the tool returns (structure of entries), how pagination works, or any behavioral constraints. For a tool that likely returns structured data, this leaves the agent with insufficient context.

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

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

Schema description coverage is 100%, so the schema fully documents both parameters. The description doesn't add any parameter-specific information beyond what's in the schema (like format examples for transcript_name or typical page_size values). The baseline score of 3 reflects adequate coverage through the schema alone.

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 ('List') and resource ('transcript entries') with additional context about the API version and that entries are 'individual speech segments'. It distinguishes from siblings like 'meet_v2_get_transcript' by specifying list vs get operations. However, it doesn't explicitly differentiate from 'meet_v2_list_transcripts' (which lists transcripts rather than entries).

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 about when to use this tool versus alternatives. The description doesn't mention prerequisites (like needing a transcript first), comparison to other listing tools, or typical use cases. The agent must infer usage from the tool name and parameters 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 but lacks behavioral details. It doesn't disclose if this is a read-only operation (implied by 'List'), pagination behavior, rate limits, authentication needs, or what the output contains (e.g., transcript IDs or summaries). The description only states the basic action without operational context.

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—a single sentence that front-loads the key action and resource. There is no wasted language, and it efficiently conveys the core purpose without unnecessary details.

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 (a list operation with no output schema) and lack of annotations, the description is incomplete. It doesn't explain return values (e.g., list of transcript objects or IDs), error conditions, or behavioral traits like pagination. For a tool with no structured output documentation, more context is needed to be fully helpful.

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 fully documents the single parameter 'conference_record_name'. The description adds no additional parameter semantics beyond implying the tool lists transcripts for a given conference record, which is already clear from the schema. 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 action ('List transcripts') and the resource ('for a conference record'), with the API version context ('Meet API v2 GA'). It distinguishes from siblings like 'meet_v2_get_transcript' (singular retrieval) and 'meet_v2_list_transcript_entries' (list entries within a transcript). However, it doesn't specify scope (e.g., all transcripts vs. filtered), making it slightly less specific than 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?

No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a conference record name), exclusions, or comparisons to siblings like 'meet_v2_list_conference_records' (which might list records first). The description assumes context but offers no explicit usage instructions.

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. It states this is an update operation, implying mutation, but doesn't disclose behavioral traits like required permissions, whether changes are reversible, rate limits, or what happens to unspecified settings. For a mutation 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 a single, efficient sentence that front-loads the key information ('Update configuration of a Google Meet space') with version context. There's zero waste or redundancy, 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 this is a mutation tool with 5 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral aspects (e.g., permissions, side effects), usage context, and output expectations. For a tool that modifies Google Meet spaces, more comprehensive guidance is needed to ensure safe and 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?

Schema description coverage is 100%, so the schema already documents all 5 parameters with descriptions and enums. The description adds no additional parameter semantics beyond what's in the schema, such as examples or constraints. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't detract.

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 ('Update configuration') and resource ('Google Meet space'), with specific version context ('Meet API v2 GA'). It distinguishes from siblings like 'meet_v2_get_space' (read) and 'meet_v2_create_space' (create), but doesn't explicitly differentiate from other update operations in the server.

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 on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing space), when not to use it, or how it differs from similar tools like 'calendar_v3_update_event'. The description is purely functional without contextual usage advice.

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