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. 'Create a new calendar event' implies a write operation, but it doesn't disclose any behavioral traits such as required permissions, whether the event is automatically saved or sent, rate limits, or what happens on failure. For a mutation tool with zero annotation coverage, 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, front-loaded sentence with zero waste: 'Create a new calendar event'. It's appropriately sized for the tool's purpose, making it easy to scan and understand quickly without 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?

Given the complexity (a mutation tool with 6 parameters), no annotations, no output schema, and 0% schema description coverage, the description is incomplete. It lacks essential context such as parameter explanations, behavioral details, usage guidelines, and return value information. This makes it insufficient for an AI agent to use the tool effectively without additional inference or trial-and-error.

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

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

The description adds no meaning beyond what the input schema provides. With schema description coverage at 0% (no parameter descriptions in the schema) and 6 parameters, the description doesn't explain any parameters like 'summary', 'start', 'end', 'attendees', 'description', or 'location'. This forces the agent to guess parameter semantics, which is inadequate for tool invocation.

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 ('create') and resource ('calendar event'), making the purpose immediately understandable. It distinguishes from siblings like 'delete_event', 'list_events', and 'update_event' by specifying it's for creation rather than deletion, listing, or modification. However, it doesn't explicitly mention what distinguishes it from other creation tools (like 'send_email' for sending emails), so it's not a perfect 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. It doesn't mention prerequisites (e.g., calendar access), when to choose 'create_event' over 'update_event' or other siblings, or any exclusions. The agent must infer usage from the tool name alone, which is insufficient for effective 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 the full burden of behavioral disclosure. It states 'Delete' which implies a destructive mutation, but doesn't specify whether this is reversible, what permissions are required, or what happens to associated data (e.g., notifications, attendees). For a destructive 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, clear sentence with zero wasted words. It's appropriately sized for a simple tool and front-loads the essential information without 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?

Given that this is a destructive mutation tool with no annotations, no output schema, and minimal parameter documentation, the description is incomplete. It doesn't address critical aspects like error conditions, confirmation requirements, or what happens post-deletion, which are essential for safe tool invocation.

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

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

The schema description coverage is 0%, so the description must compensate for undocumented parameters. It mentions 'a calendar event' which implies the 'event_id' parameter, but doesn't explain what format the ID should be, where to obtain it, or any validation rules. This adds minimal semantic value beyond what's inferred from the parameter name.

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 the resource ('a calendar event'), which provides a specific verb+resource combination. However, it doesn't differentiate this tool from its sibling 'update_event' in terms of destructive vs. non-destructive operations, which would be helpful for 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 like 'update_event' or 'create_event'. There's no mention of prerequisites (e.g., needing an event_id), exclusions, or contextual factors that would help an agent decide between this and other event-related 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 states this is a list operation but doesn't mention whether it requires authentication, has rate limits, what 'recent' means temporally, or how results are ordered. 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 gets straight to the point with no wasted words. It's appropriately sized for a simple list operation and front-loads the core functionality.

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 0% schema description coverage, the description is inadequate. It doesn't explain return format, error conditions, authentication requirements, or how parameters interact. Given the complexity of email retrieval and sibling tools, 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?

The schema description coverage is 0%, so the description must compensate. It mentions 'recent emails' but doesn't explain how the 'query' parameter works (e.g., Gmail search syntax) or what 'max_results' controls beyond its name. The description adds minimal value beyond what's implied by parameter names.

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 ('recent emails from Gmail inbox'), making the purpose immediately understandable. However, it doesn't distinguish this tool from sibling 'search_emails', which appears to be a similar email retrieval tool, so it doesn't achieve full 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 like 'search_emails' or 'modify_email'. It mentions 'recent emails' but doesn't define what 'recent' means or specify any exclusions or prerequisites for 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool lists events but doesn't cover critical aspects like authentication requirements, rate limits, pagination behavior (implied by 'max_results' but not explained), whether it returns past events, or error conditions. This is a significant gap for a tool that interacts with calendar 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 with zero wasted words. It's front-loaded with the core purpose, making it easy to scan and understand quickly. Every word earns its place by conveying 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?

Given the tool's complexity (interacting with calendar events, 3 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., event details, error formats), how to handle the time parameters, or behavioral traits like permissions needed. This leaves the agent under-informed 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 schema description coverage is 0%, meaning none of the three parameters ('max_results', 'time_max', 'time_min') are documented in the schema. The description adds no information about these parameters—it doesn't explain what 'upcoming' means relative to 'time_min'/'time_max', the format for time values, or the effect of 'max_results'. This fails to compensate for the lack of schema 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 'List upcoming calendar events' clearly states the verb ('List') and resource ('upcoming calendar events'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'search_google' or 'search_emails' that might also return calendar events, nor does it specify if it lists only the user's events or shared ones.

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 'search_google' (which might search across Google services including Calendar) or 'update_event' (for modifying events), leaving the agent to guess based on tool names 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'modify' implies a mutation operation, the description doesn't specify whether changes are reversible, what permissions are required, or how errors are handled (e.g., invalid labels). It mentions actions like 'archive' and 'trash' which suggest destructive changes, but lacks explicit warnings or context about their permanence.

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 uses parentheses to provide examples without verbosity. However, the 'etc.' is slightly vague and could be replaced with more precise terminology to improve clarity without sacrificing 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 mutation tool with 3 parameters, 0% schema coverage, no annotations, and no output schema, the description is inadequate. It fails to explain parameter semantics, behavioral implications (e.g., side effects), or expected outcomes. For a tool that modifies email states, more context on labels, ID sourcing, and result handling 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 0%, so the description must compensate for undocumented parameters. It only vaguely references 'labels' without explaining what 'add_labels' or 'remove_labels' entail, their format, or valid values (e.g., system vs. user labels). The 'id' parameter is not mentioned at all, leaving its purpose ambiguous. The description adds minimal value beyond the schema's property titles.

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 ('modify') and resource ('email labels'), and provides specific examples of modifications (archive, trash, mark read/unread). It distinguishes from obvious siblings like 'send_email' or 'list_emails' by focusing on label manipulation rather than creation or retrieval. However, it doesn't explicitly differentiate from potential overlapping tools like 'update_event' for email-related events.

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 email ID), exclusions (e.g., not for creating emails), or comparisons to siblings like 'search_emails' for finding emails to modify. 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions reading file contents but doesn't specify aspects like authentication requirements, rate limits, file size constraints, or output format (e.g., text, binary). This leaves significant gaps for a tool that interacts with an external service like Google Drive.

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

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

The description is a single, clear sentence that efficiently conveys the core purpose without unnecessary words. It's front-loaded and appropriately sized for a simple tool, with zero waste.

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 interacting with Google Drive (an external API), lack of annotations, no output schema, and incomplete parameter documentation, the description is insufficient. It doesn't cover critical aspects like authentication, error handling, or return values, making it inadequate for 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?

The input schema has 0% description coverage, and the tool description doesn't add any parameter details. It doesn't explain what 'file_id' is, how to obtain it, or any constraints (e.g., format, validity). With low schema coverage, the description fails to compensate, leaving the parameter undocumented.

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 ('Read contents') and resource ('a file from Google Drive'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'search_gdrive' or 'search_google', which might also involve reading Google Drive content, so it doesn't reach the highest 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 'search_gdrive' or 'search_google', nor does it mention any prerequisites or exclusions. It merely states what the tool does without contextual usage information.

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 'advanced query' but doesn't disclose behavioral traits such as permissions needed, rate limits, pagination, or what 'advanced' means (e.g., search operators). This leaves critical operational details unspecified.

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, making it appropriately sized and front-loaded. However, it lacks structural depth that could improve clarity without adding bulk.

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, 0% schema coverage, no output schema, and a search tool with siblings, the description is incomplete. It doesn't explain return values, error handling, or contextual nuances, leaving significant 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?

Schema description coverage is 0%, so the description must compensate. It implies a 'query' parameter but adds no meaning beyond the schema's basic titles. No details on query syntax, format, or how 'max_results' interacts with search are provided, failing to enhance parameter understanding.

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 'Search emails with advanced query' states the verb ('search') and resource ('emails'), providing a basic purpose. However, it's vague about what 'advanced query' entails and doesn't differentiate from sibling tools like 'list_emails' or 'search_google', leaving ambiguity in scope and 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?

No guidance is provided on when to use this tool versus alternatives. With siblings like 'list_emails' and 'search_google', the description lacks explicit context, prerequisites, or exclusions, offering no help in 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 the full burden of behavioral disclosure. It only states the basic action ('Search for files') without mentioning permissions, rate limits, pagination behavior (implied by page_size/page_token but not explained), or what the search returns. This leaves significant gaps for a tool with 3 parameters.

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 gets straight to the point with no wasted words. It's appropriately sized for a basic tool description, though it lacks depth due to its brevity.

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 (3 parameters, no annotations, no output schema), the description is incomplete. It doesn't cover parameter usage, behavioral traits, or output expectations. For a search tool with pagination and query parameters, more context is needed 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 0%, so the description must compensate but adds no parameter information. It doesn't explain what 'query' should contain (e.g., search syntax), what 'page_size' and 'page_token' do, or how results are structured. With 3 parameters, this is inadequate.

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 ('Search') and resource ('files in Google Drive'), making the purpose immediately understandable. However, it doesn't distinguish this tool from sibling tools like 'search_google' or 'read_gdrive_file', which might have overlapping or related 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. With sibling tools like 'search_google' (possibly broader search) and 'read_gdrive_file' (reading specific files), there's no indication of context, prerequisites, or exclusions for this search 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'return formatted results,' which adds some context about output format, but lacks details on rate limits, authentication needs, pagination, error handling, or what 'formatted' entails. For a search 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 front-loads the core action and outcome with zero wasted words. It's appropriately sized for a simple search tool, 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 moderate complexity (search operation with 2 parameters), no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits, parameter usage, and output structure. The description alone doesn't provide enough context for an agent to use the tool effectively beyond basic invocation.

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

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

The input schema has 2 parameters with 0% description coverage, so the schema provides no semantic context. The description doesn't add any parameter-specific information beyond the tool's overall function. It implies the 'query' parameter is used for the search but doesn't explain 'num_results' or other details. Baseline 3 is appropriate as the description doesn't compensate for the schema gap but doesn't mislead.

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 ('Perform') and resource ('Google search'), and specifies the outcome ('return formatted results'). It distinguishes from siblings like search_emails or search_gdrive by specifying Google search, though it doesn't explicitly contrast them. The purpose is unambiguous but lacks explicit 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 when to prefer this over other search tools (e.g., search_emails for email content) or general web search contexts. Usage is implied by the name and purpose, but no explicit when/when-not or alternative recommendations are given.

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 write operation (sending) but does not disclose permissions needed, rate limits, delivery confirmation, or error handling. 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 with a single sentence, 'Send a new email,' which is front-loaded and wastes no words. However, this conciseness comes at the cost of completeness, as it under-specifies critical 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?

For a 5-parameter mutation tool with no annotations and no output schema, the description is incomplete. It fails to address behavioral aspects, parameter meanings, or usage context, making it insufficient for reliable agent operation despite the simple action implied.

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 0%, so the description must compensate but adds no parameter details. It does not explain the purpose of fields like bcc or cc, expected formats, or constraints beyond what the schema titles imply. This leaves significant gaps in understanding the 5 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 'Send a new email' clearly states the action (send) and resource (email), distinguishing it from siblings like list_emails or modify_email. However, it lacks specificity about what constitutes 'new' versus existing emails, making it somewhat vague compared to more precise 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 is provided on when to use this tool versus alternatives like modify_email or search_emails. The description does not mention prerequisites, context, or exclusions, leaving the agent to infer usage based on tool names 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. 'Update' implies a mutation operation, but the description doesn't disclose whether this requires specific permissions, what happens to unspecified fields (partial vs. full updates), whether changes are reversible, or any rate limits. It mentions no behavioral traits beyond the basic action.

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's front-loaded with the core action ('Update an existing calendar event') and doesn't include unnecessary details. Every word earns its place, 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 complexity (7 parameters, mutation tool), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns, error conditions, or behavioral context needed for safe invocation. For a tool that modifies calendar events, this leaves significant gaps in understanding how 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?

The description adds zero meaning beyond what the input schema provides. With 7 parameters and 0% schema description coverage, the schema only provides titles like 'Attendees' and 'Description' without explaining what these parameters do, their formats, or constraints. The description doesn't compensate by explaining any parameters, leaving all semantics undocumented.

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 ('an existing calendar event'), making the purpose immediately understandable. It distinguishes from sibling tools like 'create_event' and 'delete_event' by specifying it's for existing events. However, it doesn't specify what aspects can be updated beyond the generic term.

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 (like needing an event_id), when not to use it, or how it differs from similar tools like 'modify_email' or 'create_event' in the sibling list. The agent must infer usage from the tool name alone.

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