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

With no annotations provided, the description carries full burden for behavioral disclosure. While 'Create' implies a write operation, the description doesn't address permissions needed, whether duplicates are allowed, what happens on failure, or what the output contains. This leaves significant behavioral questions unanswered.

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

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

The description is appropriately concise with a clear purpose statement followed by parameter documentation. The Args section is well-structured and easy to parse. Minor formatting issues with indentation slightly detract from perfect structure.

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 write operation with no annotations and 4 parameters, the description provides adequate parameter semantics but lacks behavioral context. The presence of an output schema means the description doesn't need to explain return values, but it should address more about the creation operation's behavior and constraints.

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 provides clear parameter documentation in the Args section, explaining what each parameter represents. With 0% schema description coverage, this documentation fully compensates by adding essential semantic meaning beyond the bare schema. Only minor formatting issues prevent a perfect 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 ('Create') and resource ('contact'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'update_contact' or specify what makes this creation operation unique versus 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?

The description provides no guidance on when to use this tool versus alternatives like 'update_contact' or 'search_contacts'. There's no mention of prerequisites, constraints, or typical use cases for creating versus other contact operations.

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

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

With no annotations provided, the description carries full burden but only states the action ('Delete') without disclosing critical behavioral traits such as whether deletion is permanent, requires specific permissions, has side effects, or what happens on success/failure. This is inadequate for a destructive operation.

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

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

The description is appropriately sized with two sentences: one for the purpose and one for the parameter. It's front-loaded with the main action, though the parameter section could be more integrated. No wasted words.

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

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

For a destructive tool with no annotations, 0% schema coverage, and an output schema (which helps but isn't described), the description is incomplete. It lacks behavioral context, error handling, and usage guidance, making it insufficient for safe agent 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 0%, so the description must compensate. It adds the parameter name and clarifies it's a 'Contact resource name (people/*)', providing basic semantics beyond the schema's title. However, it doesn't explain format details or validation rules, leaving gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Delete') and resource ('a contact'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'update_contact' or 'create_contact' beyond the obvious action difference, missing explicit sibling 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?

No guidance is provided on when to use this tool versus alternatives like 'update_contact' or 'create_contact', nor any context about prerequisites or exclusions. The description only states what it does, not when it's 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves a contact but doesn't describe what happens if the contact isn't found (e.g., error handling), authentication needs, rate limits, or the format of the output. For a read operation with zero annotation coverage, 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 appropriately sized and front-loaded, with the core purpose stated clearly in the first sentence. The additional parameter explanation is concise and directly relevant. There's no wasted text, though the structure could be slightly improved by integrating the parameter details more seamlessly.

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

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

Given the tool's low complexity (single parameter, read operation) and the presence of an output schema, the description is somewhat complete but has gaps. It covers the basic purpose and parameter semantics adequately, but without annotations, it lacks behavioral details like error handling. The output schema likely explains return values, reducing the burden on the description.

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 meaningful context beyond the input schema, which has 0% description coverage. It explains that the 'identifier' parameter can be either a resource name (people/*) or an email address, clarifying the two valid input types. This compensates well for the schema's lack of detail, though it doesn't specify format constraints or examples.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get a contact by resource name or email.' It specifies the verb ('Get') and resource ('contact'), and distinguishes it from siblings like list_contacts or search_contacts by focusing on retrieving a single contact. However, it doesn't explicitly differentiate from get_other_contacts, which might have overlapping functionality.

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

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

The description provides no guidance on when to use this tool versus alternatives. With siblings like list_contacts, search_contacts, and get_other_contacts, there's no indication of when this specific retrieval method is preferred, such as for known identifiers versus broader searches. It lacks context on 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. It states this is a retrieval operation, implying read-only behavior, but doesn't disclose other behavioral traits such as authentication requirements, rate limits, pagination, error handling, or what the output contains. The description adds minimal context beyond the 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 appropriately sized with three sentences: the first states the purpose, the second explains 'Other contacts', and the third documents the parameter. It's front-loaded with the main action, and each sentence adds value without redundancy. Minor improvements could include more structured formatting.

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 has one parameter and an output schema exists, the description covers the basics but lacks depth. It explains what 'Other contacts' are and documents the parameter, but without annotations, it misses behavioral context like safety or performance traits. The output schema likely handles return values, so completeness is adequate but not thorough.

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?

With 0% schema description coverage, the description compensates by documenting the single parameter 'max_results' with its default value and purpose. This adds meaningful semantics beyond the schema, which only provides the title and type. However, it doesn't specify constraints like minimum/maximum values or format details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'retrieve' and the resource 'contacts from the Other contacts section', with additional context explaining what 'Other contacts' are. However, it doesn't explicitly differentiate from sibling tools like list_contacts or search_contacts, which likely retrieve different contact sets.

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 by explaining that 'Other contacts' are people interacted with but not in the main contacts list, suggesting this tool is for retrieving that specific subset. However, it doesn't provide explicit guidance on when to use this versus alternatives like list_contacts or search_contacts, nor does it mention any 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 full burden for behavioral disclosure. It mentions filtering and pagination (via max_results), but doesn't cover important aspects like whether this requires authentication, rate limits, sorting behavior, error conditions, or what happens when no matches are found. For a listing tool with no 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 appropriately concise with a clear purpose statement followed by parameter explanations. The two-sentence structure is efficient, though the formatting with extra whitespace could be cleaner. Every sentence adds value 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 the tool has an output schema (which handles return values), 2 parameters with good description coverage, and no complex annotations, the description is reasonably complete for a basic listing tool. However, it lacks guidance on sibling tool differentiation and some behavioral context that would be helpful for an agent making informed decisions.

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?

With 0% schema description coverage, the description fully compensates by explaining both parameters: 'name_filter' as an optional filter for contacts by name, and 'max_results' as the maximum number of results with its default value. This adds meaningful context beyond the bare schema, though it doesn't specify exact matching behavior (exact vs. partial, case sensitivity).

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: 'List all contacts or filter by name.' This specifies the verb ('List') and resource ('contacts') with optional filtering. However, it doesn't explicitly differentiate from sibling tools like 'search_contacts' or 'get_other_contacts,' which likely have overlapping functionality.

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

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

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'search_contacts' and 'get_other_contacts' available, there's no indication of when this listing/filtering approach is preferred over those other methods. The description only states what the tool does, not when to choose it.

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 it mentions the tool 'allows you to search and list users' and describes parameters, it doesn't cover important behavioral aspects like authentication requirements, rate limits, pagination behavior, error conditions, or what specific user information beyond email addresses is returned. For a directory listing 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 appropriately sized and well-structured with clear sections. The purpose is stated upfront, followed by additional context, then parameter explanations. While slightly verbose with some redundancy ('list' appears twice in the opening), each sentence adds value and there's no wasted text. The parameter documentation is neatly formatted.

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

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

Given that an output schema exists (so return values are documented elsewhere), the description covers the basic purpose and parameters adequately. However, for a directory listing tool with no annotations and multiple sibling tools, it should provide more context about when to use it versus alternatives and more behavioral transparency about how it operates. The parameter explanations help compensate for the 0% schema coverage.

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?

With 0% schema description coverage, the description compensates well by explaining both parameters: 'query' is described as 'Optional search term to find specific users (name, email, etc.)' and 'max_results' as 'Maximum number of results to return (default: 50)'. This adds meaningful context beyond the bare schema, clarifying the query scope and default value. However, it doesn't specify format constraints or validation rules.

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: 'List Google Workspace users in your organization's directory' with the verb 'list' and resource 'Google Workspace users'. It specifies the scope ('your organization's directory') and mentions what information is included ('email addresses and other information'). However, it doesn't explicitly differentiate from sibling tools like 'search_directory' or 'list_contacts', which appear to be related directory/search tools.

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_directory', 'list_contacts', and 'search_contacts' available, there's no indication of when this specific workspace user listing tool is appropriate versus those other directory/contact tools. The description only states what the tool does, not when to choose it.

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 searches contacts but doesn't mention important behavioral aspects like whether it's read-only, requires authentication, has rate limits, returns paginated results, or what happens on errors. For a search tool with zero 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 appropriately sized and front-loaded with the core purpose in the first sentence. The parameter explanations are brief and directly relevant. There's no wasted text, and the structure is clear and efficient.

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 there's an output schema (which handles return values), the description covers the basic purpose and parameters adequately. However, for a search tool with no annotations and multiple sibling tools, it lacks context about behavioral traits and usage differentiation, making it only minimally complete.

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

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

The description adds meaningful context beyond the input schema. While schema description coverage is 0%, the description explains that 'query' searches 'by name, email, or phone number' and that 'max_results' has a default of 10. This compensates well for the lack of schema descriptions, though it doesn't cover all possible parameter nuances.

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: 'Search contacts by name, email, or phone number.' This specifies the verb (search), resource (contacts), and searchable fields. However, it doesn't explicitly differentiate from sibling tools like 'list_contacts' or 'search_directory', which would be needed for 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 'list_contacts', 'get_contact', or 'search_directory'. It mentions what the tool does but gives no context about appropriate use cases, prerequisites, or exclusions.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'more targeted search' which hints at specificity, but doesn't describe important behaviors like authentication requirements, rate limits, pagination, error handling, or what constitutes a 'targeted' search. For a search tool with zero annotation coverage, this leaves significant gaps in understanding how it operates.

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 well-structured and appropriately sized. It starts with the core purpose, adds context about the search type, and then provides parameter details in a clear format. Every sentence adds value, though the 'more targeted search' phrase could be more specific to earn a perfect score.

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 there's an output schema (which handles return values) and only 2 parameters with good description coverage, the description is reasonably complete for a search tool. However, the lack of annotations means important behavioral aspects like authentication, rate limits, and error handling aren't addressed, and the relationship to sibling tools isn't clarified, leaving some contextual 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?

The description adds meaningful context for both parameters beyond what the schema provides. It explains that 'query' is a 'Search term to find specific directory members' and 'max_results' has a 'default: 20', which clarifies their purpose and usage. Since schema description coverage is 0%, the description effectively compensates by providing this essential parameter 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 tool's purpose: 'Search for people specifically in the Google Workspace directory.' It specifies the verb ('search'), resource ('people'), and scope ('Google Workspace directory'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'search_contacts' or 'list_workspace_users', which prevents a perfect score.

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

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

The description provides some implied usage context by mentioning 'more targeted search' and specifying the directory scope, which suggests it's for organizational directory searches rather than general contacts. However, it lacks explicit guidance on when to use this tool versus alternatives like 'search_contacts' or 'list_workspace_users', and doesn't mention any 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 the full burden of behavioral disclosure. It states this is an update operation, implying mutation, but doesn't mention permissions, reversibility, error handling, or rate limits. The description adds minimal behavioral context beyond the basic action, which is insufficient for a mutation tool without 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 front-loaded with the core purpose in the first sentence, followed by a structured parameter list. It avoids unnecessary fluff, though the parameter explanations are minimal and could be more informative without sacrificing 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 tool's complexity (mutation with 5 parameters), no annotations, and an output schema (which reduces the need to describe return values), the description is partially complete. It covers the basic action and parameters but lacks critical context like usage guidelines, behavioral details, and parameter nuances, making it adequate but with clear 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 0%, so the description must compensate. It lists all 5 parameters with brief explanations (e.g., 'Updated first name'), adding some meaning beyond the schema's titles. However, it doesn't clarify format expectations (e.g., email validation) or the implications of null values, leaving gaps in 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 clearly states the verb ('Update') and resource ('an existing contact'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its siblings like 'create_contact' or 'delete_contact' beyond the basic action, missing explicit comparison that would warrant 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 'create_contact' or 'delete_contact'. It lacks context about prerequisites (e.g., needing an existing contact resource) or exclusions, leaving the agent to 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.