Google Workspace MCP Server

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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes targeting specific Google Workspace services (Docs, Gmail, Calendar, etc.), with clear boundaries. However, some overlap exists, such as get_doc_content and get_drive_file_content for document retrieval, and multiple comment tools (create_document_comment, read_document_comments, etc.) that could cause confusion if not carefully distinguished by context.
Naming Consistency5/5
Tool names follow a highly consistent snake_case pattern with clear verb_noun conventions (e.g., create_doc, modify_event, list_calendars). The naming is uniform across all 84 tools, making it predictable and easy to understand the action and target resource for each tool.
Tool Count2/5
With 84 tools, the set is excessively large for a single server, making it overwhelming and difficult for agents to navigate efficiently. While Google Workspace is broad, this count suggests poor scoping, as many tools could be consolidated or split into focused sub-servers (e.g., separate servers for Docs, Gmail, Calendar) to improve usability.
Completeness5/5
The tool set provides comprehensive coverage across Google Workspace services, including full CRUD operations for Docs, Sheets, Slides, Calendar, Gmail, Drive, Tasks, and Forms. It supports complex workflows (e.g., batch operations, document structure inspection) and integrates auxiliary functions like search and authentication, leaving no obvious gaps for the domain.
Average 3.4/5 across 84 of 84 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
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{
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  ]
}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior1/5
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 but fails to do so. It doesn't mention whether this action is destructive, requires specific permissions, has side effects, or what the output looks like. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no wasted words. It's appropriately sized and front-loaded, making it easy to parse quickly without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that this is a mutation tool with no annotations, 0% schema coverage, and three required parameters, the description is insufficient. While an output schema exists, the description doesn't address behavioral aspects like permissions, side effects, or error conditions, leaving critical gaps for agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the three parameters (comment_id, document_id, user_google_email) are documented in the schema. The description adds no information about what these parameters mean, their format, or how to obtain them, failing to compensate for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Resolve') and target resource ('a comment in a Google Document'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'resolve_presentation_comment' or 'resolve_spreadsheet_comment', which perform similar operations on different document types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'reply_to_document_comment' or 'clear_completed_tasks'. The description lacks context about prerequisites, such as needing existing comments or appropriate permissions, leaving usage unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior but only states the action without details. It does not cover permissions required, whether resolution is reversible, effects on the presentation or comment thread, rate limits, or error handling. This leaves significant gaps in understanding the tool's operational traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, straightforward sentence with no unnecessary words. It is front-loaded with the core action and target, making it efficient and easy to parse, though this brevity contributes to gaps in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 parameters), lack of annotations, and 0% schema coverage, the description is insufficient. While an output schema exists, the description does not address behavioral aspects, parameter meanings, or usage context, leaving the tool inadequately documented for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 does not explain the meaning or format of 'comment_id', 'presentation_id', or 'user_google_email', nor their relationships. This fails to address the undocumented parameters, resulting in inadequate semantic clarity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action ('Resolve') and target ('a comment in a Google Presentation'), which clarifies the tool's purpose. However, it lacks specificity about what 'resolve' entails (e.g., marking as resolved, deleting, archiving) and does not differentiate from sibling tools like 'resolve_document_comment' or 'resolve_spreadsheet_comment', making it vague in comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 does not mention prerequisites (e.g., needing comment access), exclusions, or comparisons to similar tools such as 'reply_to_presentation_comment' or 'read_presentation_comments', leaving usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. 'Resolve' implies a mutation (likely marking a comment as resolved), but the description doesn't specify what 'resolve' entails (e.g., closing the comment, changing its status), whether it requires specific permissions, or what the output might be. This is a significant gap 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.
Conciseness5/5
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 and resource, making it easy to parse quickly, though this brevity contributes to gaps in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's mutation nature (implied by 'resolve'), lack of annotations, and 0% schema description coverage, the description is incomplete. While an output schema exists (which might cover return values), the description doesn't address key aspects like behavioral effects, parameter meanings, or usage context, making it inadequate for safe and effective tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter details. The description adds no information about the three required parameters (comment_id, spreadsheet_id, user_google_email), such as their formats, sources, or relationships. It fails to compensate for the lack of schema descriptions, leaving parameters entirely undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action ('resolve') and resource ('comment in a Google Spreadsheet'), which is clear but basic. It doesn't distinguish this tool from sibling tools like 'resolve_document_comment' or 'resolve_presentation_comment' beyond specifying the spreadsheet context, leaving some ambiguity about its unique scope among similar comment-resolution tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 comment access), exclusions, or comparisons to sibling tools like 'reply_to_spreadsheet_comment', leaving the agent to infer usage context solely from the tool name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 Drive API and mimeType filter but doesn't cover important aspects like authentication requirements, rate limits, pagination behavior (despite having a page_size parameter), error conditions, or whether this is a read-only operation. The return format is mentioned but lacks detail about structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately brief with two sentences that convey the core functionality and return format. The information is front-loaded with the main purpose stated first. However, the second sentence about return format could be more specific about what 'formatted list' means.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with 3 parameters, 0% schema coverage, no annotations, and multiple similar sibling tools, the description is inadequate. While an output schema exists (which reduces the need to document return values), the description fails to provide necessary context about parameter usage, differentiation from alternatives, and behavioral expectations like authentication or pagination.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and 3 parameters, the description provides no information about any parameters. It doesn't explain what the 'query' parameter should contain, how 'user_google_email' is used, or what 'page_size' controls. The description mentions 'by name' which might imply something about the query parameter, but this is insufficient compensation for the complete lack of parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Searches for Google Docs') and resource ('by name using Drive API'), and mentions the mimeType filter which adds specificity. However, it doesn't explicitly differentiate from sibling tools like 'search_drive_files' or 'list_docs_in_folder', which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like 'search_drive_files' or 'list_docs_in_folder'. The description mentions the mimeType filter but doesn't explain when this specific search approach is preferred over other search methods available in sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'Sends a message' and returns a confirmation, implying a write operation, but fails to mention critical details like required permissions (e.g., Google Chat access), rate limits, error conditions, or whether the action is reversible. 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded, with the core purpose stated in the first sentence and return details in the second. There's no unnecessary verbiage, and it efficiently conveys the basic action. However, the return statement could be integrated more seamlessly, and the overall brevity comes at the cost of completeness, slightly affecting its effectiveness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 4 parameters), lack of annotations, and 0% schema description coverage, the description is insufficiently complete. It doesn't explain parameter meanings, behavioral constraints, or usage context, and while an output schema exists (implied by 'Returns: str'), the description's minimal detail doesn't adequately support an AI agent in selecting or invoking this tool correctly amidst many siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the 4 parameters are documented in the schema. The description adds no parameter semantics beyond the return value, failing to explain what 'space_id', 'thread_key', or 'user_google_email' represent or how they should be used. This leaves key inputs ambiguous, such as whether 'user_google_email' is the sender or recipient, and doesn't compensate for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Sends a message to a Google Chat space.' It specifies the verb ('Sends') and resource ('message to a Google Chat space'), making the action unambiguous. However, it doesn't differentiate from sibling tools like 'send_gmail_message' or 'search_messages', 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.
Usage Guidelines2/5
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 'send_gmail_message' for email or 'search_messages' for retrieval, nor does it specify prerequisites or contextual cues (e.g., use for real-time chat vs. other communication methods). This lack of comparative or conditional advice limits its utility for an AI agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 return type ('str: Formatted messages') but doesn't cover critical aspects like pagination behavior (implied by 'page_size' parameter), rate limits, authentication needs, or whether it's a read-only operation. This leaves significant gaps for an agent to understand how to invoke it effectively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the main action, followed by a return statement. It avoids unnecessary words, but the second sentence could be integrated more smoothly (e.g., 'Retrieves and returns formatted messages...'). Overall, it's efficient but not perfectly structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 likely covers return values), the description doesn't need to detail outputs. However, with 4 parameters, 0% schema coverage, and no annotations, the description should provide more context about parameter meanings and behavioral traits. It's minimally adequate but has clear gaps in guiding usage and transparency.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter details. The description adds no information about the four parameters (e.g., what 'space_id' or 'user_google_email' represent, how 'order_by' works, or what 'page_size' controls). This fails to compensate for the lack of schema documentation, leaving parameters largely unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'retrieves' and the resource 'messages from a Google Chat space', making the purpose evident. However, it doesn't differentiate from sibling tools like 'search_messages' or 'send_message', 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.
Usage Guidelines2/5
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 'search_messages' or 'list_spaces'. The description lacks context about prerequisites, such as needing a specific space ID or user email, which are required parameters but not explained in usage terms.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 the return type ('str: A formatted list') but lacks critical details: it doesn't specify if this is a read-only operation, whether it requires specific permissions, how pagination works with 'page_size', or potential rate limits. For a tool with 3 parameters and no 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately concise with two sentences: one for the purpose and one for the return value. It's front-loaded with the core functionality, and there's no redundant information. However, the return statement could be integrated more smoothly, but it doesn't detract significantly from clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, no annotations, but has an output schema), the description is partially complete. It states the purpose and return format, but lacks parameter explanations, usage context, and behavioral details. The output schema existence means return values are documented elsewhere, but overall, it's inadequate for full understanding without external schema references.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter details. The description adds no information about the parameters—it doesn't explain what 'page_size', 'space_type', or 'user_google_email' mean, their valid values, or how they affect the listing. With 3 parameters and low coverage, the description fails to compensate, leaving semantics unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Lists Google Chat spaces (rooms and direct messages) accessible to the user.' It specifies the verb ('Lists'), resource ('Google Chat spaces'), and scope ('accessible to the user'), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'list_calendars' or 'list_docs_in_folder', 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.
Usage Guidelines2/5
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 needs), compare to similar tools like 'list_drive_items', or specify scenarios where this tool is preferred. The agent must infer usage from the purpose alone, which is insufficient for optimal selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 action ('Reply to') but doesn't cover critical aspects like required permissions (e.g., edit access to the presentation), whether replies are editable/deletable, rate limits, or error conditions (e.g., invalid comment_id). For a mutation tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place by conveying essential purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (a mutation with 4 required parameters), no annotations, and 0% schema coverage, the description is incomplete. However, the presence of an output schema reduces the need to explain return values. The description covers the basic action but lacks details on parameters, behavioral traits, and usage context, making it minimally adequate but with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the 4 parameters have descriptions in the schema. The tool description provides no additional information about parameter meanings (e.g., what format comment_id or presentation_id should be, whether user_google_email must match the authenticated user). This leaves all parameters undocumented, failing to compensate for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Reply to') and resource ('a specific comment in a Google Presentation'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'reply_to_document_comment' or 'reply_to_spreadsheet_comment', which perform similar actions on different Google Workspace resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 comment access), exclusions, or comparisons to sibling tools like 'resolve_presentation_comment' or 'create_presentation_comment', leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 the return type ('A formatted list of messages') but lacks critical details: whether this is a read-only operation, if it requires specific permissions, rate limits, pagination behavior (despite a 'page_size' parameter), or error conditions. For a search 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded, with the core purpose stated in the first sentence. The second sentence adds return value information efficiently. There's no wasted text, though it could be more comprehensive without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, 2 required), no annotations, 0% schema description coverage, but with an output schema present, the description is partially complete. It covers the basic purpose and return format, but misses parameter explanations, usage context, and behavioral details. The output schema helps, but gaps remain for effective tool selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter documentation. The description adds no information about the four parameters (query, space_id, user_google_email, page_size), such as what the query syntax is, whether space_id is optional, or what user_google_email represents. It fails to compensate for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Searches for messages in Google Chat spaces by text content.' This specifies the verb ('searches'), resource ('messages'), and scope ('Google Chat spaces'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'search_gmail_messages' or 'search_docs', 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.
Usage Guidelines2/5
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_gmail_messages' for email or 'search_docs' for documents, nor does it specify prerequisites or appropriate contexts. 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.
Behavior2/5
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 'batch updates' implying mutation, but doesn't disclose critical behaviors: whether updates are atomic, if there are rate limits, what happens on partial failures, or authentication requirements beyond the email parameter. For a mutation tool with zero annotation coverage, this is a significant gap in 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, Args, Returns) and avoids redundancy. The first sentence directly states the tool's function, and subsequent sections are organized. It could be slightly more concise by integrating the Args explanation into the main text, but overall it's efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (batch mutation with 3 parameters), no annotations, and 0% schema coverage, the description is moderately complete. It covers basic purpose and parameters but lacks behavioral details and usage context. The output schema exists (implied by Returns), so describing return values isn't needed, but other gaps remain for a mutation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter documentation. The description lists parameters in the Args section with basic types, adding minimal semantics (e.g., 'user_google_email' as 'The user's Google email address'). However, it doesn't explain the structure of 'requests' or provide examples, leaving key details unclear. This partially compensates but doesn't fully address the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Apply batch updates') and resource ('to a Google Slides presentation'), making the purpose unambiguous. It distinguishes from siblings like 'create_presentation' or 'get_presentation' by focusing on batch updates, though it doesn't explicitly differentiate from similar tools like 'batch_update_doc' beyond the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 edit permissions), compare to single-update methods, or specify use cases like bulk formatting changes. With many sibling tools, this lack of context leaves the agent guessing about appropriate scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but provides minimal behavioral context. It mentions the creation action and optional content insertion, but doesn't disclose permissions needed (Google Docs API access), whether the document is created in a specific location (Drive root vs. folder), rate limits, or what happens if creation fails. The return format is mentioned but without details about error cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that efficiently state the core functionality and return value. The first sentence clearly states the primary action with optional feature, and the second describes the return format. No wasted words, though it could be slightly more structured with bullet points for parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a mutation tool with no annotations, 3 parameters with 0% schema coverage, and an output schema present, the description provides basic completeness but with significant gaps. It covers the core action and return format (output schema handles details), but misses important context about permissions, error handling, and parameter semantics that would be needed for reliable tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 only partially does. It explains that 'content' is 'optional initial content' which adds meaning beyond the schema's generic 'Content' title, but provides no context for 'title' or 'user_google_email' parameters. With 3 parameters and low schema coverage, this leaves significant gaps in understanding parameter purposes.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Creates a new Google Doc') and resource ('Google Doc'), with additional detail about optional content insertion. It distinguishes from siblings like 'create_drive_file' by specifying document type, though not explicitly contrasting with 'create_spreadsheet' or 'create_presentation' which are also Google Workspace creation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like 'create_drive_file' (general file creation) or other Google Doc-specific tools. The description mentions optional content insertion but doesn't provide context about when this is preferable over creating an empty document and using 'insert_doc_elements' later.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. While 'Create' implies a write/mutation operation, the description doesn't disclose important behavioral traits like required permissions, whether the comment is immediately visible, how it interacts with existing comments, rate limits, or what happens on failure. For a mutation tool with zero annotation coverage, this represents a significant gap in behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 zero wasted words. It's appropriately sized for a tool with a straightforward purpose and follows good front-loading principles by immediately stating the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 means the description doesn't need to explain return values) and the tool has moderate complexity (3 required parameters for a mutation operation), the description is minimally adequate but incomplete. The presence of an output schema helps, but the complete lack of parameter semantics and behavioral context for a mutation tool leaves significant gaps in understanding how to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 have descriptions in the schema. The tool description provides no information about what the parameters mean, their expected formats, or how they relate to each other. The description doesn't compensate for the complete lack of schema documentation, leaving all three required parameters (comment_content, document_id, user_google_email) semantically undefined.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create a new comment') and target resource ('on a Google Document'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from sibling tools like 'create_presentation_comment' or 'create_spreadsheet_comment' that perform similar operations on different Google Workspace resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance about when to use this tool versus alternatives. There are sibling tools for creating comments on presentations and spreadsheets, but the description doesn't mention these alternatives or provide context about when this specific document comment tool is appropriate versus other comment-related tools like 'reply_to_document_comment' or 'resolve_document_comment'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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/mutation operation, the description doesn't address permissions needed, whether comments are public/private, rate limits, or what the output contains. It provides minimal behavioral context 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core functionality without unnecessary words. It's appropriately sized for a basic tool description and front-loads the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 no annotations, the description provides minimal but adequate context for a simple creation tool. However, with 3 undocumented parameters and no behavioral guidance, it leaves significant gaps that the agent must infer from the tool name and schema structure alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so all 3 parameters are undocumented in the schema. The description adds no information about parameter meanings, formats, or constraints. It doesn't explain what 'presentation_id' should look like, what 'comment_content' can contain, or why 'user_google_email' is required for comment creation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create a new comment') and target resource ('on a Google Presentation'), providing specific verb+resource pairing. However, it doesn't distinguish this tool from sibling comment tools like 'create_document_comment' or 'create_spreadsheet_comment', which follow the same pattern for different Google Workspace apps.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 sibling tools like 'reply_to_presentation_comment' or 'resolve_presentation_comment', nor does it specify prerequisites (e.g., needing edit access to the presentation) or appropriate contexts for comment creation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. While 'Create' implies a write/mutation operation, the description doesn't address important behavioral aspects like required permissions, whether comments are public or private, if there are rate limits, what happens on failure, or what the tool returns. The description is minimal and lacks behavioral context needed for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 zero wasted words. It's appropriately sized for a basic operation and front-loads the essential information about what the tool does.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 means return values are documented elsewhere) and the tool has moderate complexity (3 required parameters for a write operation), the description is incomplete. While concise, it doesn't provide enough context about behavioral aspects, parameter meanings, or usage guidelines that would help an agent use this tool correctly and safely.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage for all 3 parameters, the description provides no parameter information whatsoever. It doesn't explain what 'comment_content' should contain, how to obtain a valid 'spreadsheet_id', or what format 'user_google_email' requires. The description fails to compensate for the complete lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create') and target resource ('a new comment on a Google Spreadsheet'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'create_document_comment' or 'create_presentation_comment' that perform similar operations on different Google Workspace file types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. There's no mention of prerequisites, when this tool is appropriate versus other comment-related tools (like 'reply_to_spreadsheet_comment' or 'read_spreadsheet_comments'), or any context about required permissions or access levels.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. While 'Get' implies a read operation, the description doesn't disclose important behavioral aspects like authentication requirements (Google email parameter suggests auth needed), rate limits, error conditions, or what happens with invalid form IDs. The Returns section describes output but doesn't cover behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with clear sections (Args, Returns). The purpose statement is front-loaded, though extremely brief. The structure is logical with parameter explanations following the main statement. No wasted sentences, though the initial 'Get a form' could be more informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 2 parameters with 0% schema coverage and no annotations, the description does provide parameter semantics and return value information. However, for a tool that likely requires authentication and interacts with Google Forms API, it lacks important context about permissions, error handling, and behavioral constraints. The output schema exists (implied by Returns section), so return values are covered adequately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates well by explaining both parameters in the Args section. It clarifies that user_google_email is 'The user's Google email address' and form_id is 'The ID of the form to retrieve', adding meaningful context beyond the bare schema. For 2 parameters with 0% schema coverage, this provides good semantic clarification.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Get a form' which is a clear verb+resource combination, but it's extremely basic and doesn't differentiate from sibling tools like 'get_form_response' or 'get_presentation'. It doesn't specify what kind of form (Google Forms) or provide any distinguishing characteristics beyond the minimal statement of purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With sibling tools like 'get_form_response' and 'list_form_responses', the description gives no indication of when this retrieval tool is appropriate versus those response-focused tools. There's no mention of prerequisites, context, or comparison to similar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves content (implying read-only) and mentions the return format ('formatted for reading'), but lacks details on permissions, rate limits, error handling, or whether it requires specific Gmail access scopes. For a tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, Args, Returns) and uses minimal sentences. Every sentence adds value: the first states the purpose, the Args explain parameters, and the Returns clarifies output. It could be slightly more concise by integrating the Args into the main text, but overall it's efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, no annotations, but has an output schema), the description is partially complete. It covers the purpose and parameters, and the output schema handles return values, but it lacks behavioral context (e.g., auth needs, error cases) and usage guidelines compared to siblings. For a read operation with output schema, it's adequate but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes an 'Args' section that explains both parameters: thread_id ('The unique ID of the Gmail thread to retrieve') and user_google_email ('The user's Google email address. Required.'). However, with 0% schema description coverage, the schema provides no additional documentation. The description compensates adequately by documenting both parameters, but doesn't elaborate on format (e.g., thread_id structure) beyond basic semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Retrieves the complete content of a Gmail conversation thread, including all messages.' It specifies the verb (retrieves), resource (Gmail thread content), and scope (complete with all messages). However, it doesn't explicitly differentiate from sibling tools like 'get_gmail_message_content' or 'get_gmail_threads_content_batch', 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.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_gmail_message_content' (for single messages) or 'get_gmail_threads_content_batch' (for multiple threads), nor does it specify prerequisites or contextual constraints beyond the required parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves details, implying a read-only operation, but doesn't clarify aspects like authentication needs (e.g., whether the user_google_email must have access permissions), rate limits, error handling, or what happens if the page doesn't exist. The mention of 'Returns: str' in the description adds minimal value since an output schema exists, leaving significant gaps in 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized, with a clear purpose statement followed by 'Args:' and 'Returns:' sections. Each sentence serves a purpose without redundancy, such as specifying required parameters and the return type. It could be slightly more front-loaded by integrating the parameter explanations into the main description, but overall, it's efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, no annotations, but with an output schema), the description is partially complete. It covers the basic purpose and parameters, and the existence of an output schema means it doesn't need to detail return values. However, it lacks usage guidelines and sufficient behavioral context (e.g., error cases, permissions), making it adequate but with clear gaps that could hinder an AI agent's effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description lists the three parameters (user_google_email, presentation_id, page_object_id) and briefly explains their roles, such as 'The user's Google email address' and 'The object ID of the page/slide to retrieve.' However, with 0% schema description coverage, it doesn't fully compensate by providing detailed semantics like format examples (e.g., email validation, ID patterns) or interdependencies. This results in a baseline score, as the description adds some meaning but falls short of comprehensive parameter guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 details about a specific page (slide) in a presentation.' It specifies the verb ('Get details') and resource ('page/slide in a presentation'), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_presentation' or 'get_page_thumbnail', which is why it doesn't 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.
Usage Guidelines2/5
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 such as 'get_presentation' (which might retrieve overall presentation details) or 'get_page_thumbnail' (which might provide visual previews), nor does it specify prerequisites or exclusions for usage. This lack of contextual direction limits its effectiveness for an AI agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 retrieves details (implying a read-only operation), it doesn't clarify authentication needs, rate limits, error conditions, or what happens if the presentation doesn't exist. The description is minimal and lacks critical behavioral context for a tool with required parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized, with a clear purpose statement followed by separate 'Args' and 'Returns' sections. Every sentence adds value: the first states the tool's function, and the subsequent sections document inputs and outputs efficiently. It could be slightly more concise by integrating the sections into a single paragraph, but the structure enhances readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 (implied by 'Has output schema: true'), the description doesn't need to detail return values, and it appropriately summarizes them as 'Details about the presentation including title, slides count, and metadata.' However, for a tool with no annotations and 2 required parameters, the description lacks completeness in behavioral aspects like error handling or usage context, leaving gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates by documenting both parameters in the 'Args' section: 'user_google_email' and 'presentation_id'. It adds meaning by specifying that the email is required and belongs to the user, and that the ID identifies the presentation to retrieve. However, it doesn't explain format expectations (e.g., email validation, ID structure) beyond what the schema titles imply.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 details about a Google Slides presentation.' It specifies the verb ('Get details') and resource ('Google Slides presentation'), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_spreadsheet_info' or 'get_doc_content' that serve similar purposes for different Google Workspace resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_presentation_comment' or 'read_presentation_comments' that might be relevant for presentation-related tasks, nor does it specify prerequisites or contextual constraints beyond the required parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 task details, implying a read-only operation, but doesn't address permissions, rate limits, error handling, or data freshness. For a tool with zero annotation coverage, this lack of behavioral context is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized. It front-loads the purpose ('Get details of a specific task') and efficiently organizes parameter and return information in labeled sections. Every sentence serves a clear purpose, with minimal redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 required parameters) and the presence of an output schema (implied by 'Returns' section), the description is partially complete. It covers the basic purpose and parameters but lacks behavioral details (e.g., permissions, errors) and doesn't fully leverage the output schema to explain return values beyond a high-level summary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The description compensates by listing parameters in the 'Args' section with brief explanations (e.g., 'The user's Google email address'), adding meaningful context beyond the schema's titles. However, it doesn't detail parameter formats, constraints, or examples, leaving some ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 details of a specific task.' It uses a specific verb ('Get') and resource ('task'), making the function unambiguous. However, it doesn't explicitly distinguish this tool from sibling tools like 'get_task_list' or 'list_tasks,' 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.
Usage Guidelines2/5
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 'list_tasks' (for listing multiple tasks) or 'get_task_list' (for retrieving task lists), nor does it specify prerequisites or contexts for usage. This leaves the agent without clear direction on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 the return format ('A formatted list'), which adds some value, but doesn't cover critical aspects like pagination behavior (despite a 'page_size' parameter), authentication requirements, rate limits, error conditions, or whether this is a read-only operation. For a tool with no annotations, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and well-structured: two sentences that directly state the purpose and return value without any fluff. Every word earns its place, and the information is front-loaded, making it easy to scan and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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), no annotations, and low schema coverage, the description is minimally adequate but has clear gaps. It covers the basic purpose and return format, but doesn't provide enough context for parameters, usage guidelines, or behavioral traits. For a tool with three parameters and no annotations, it should do more to be fully helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 mentions 'specific Drive folder', which loosely relates to 'folder_id', but doesn't explain the other two parameters ('page_size' and 'user_google_email') or their purposes. The description adds minimal value beyond what's inferred from parameter names, failing to adequately address the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Lists Google Docs within a specific Drive folder.' It specifies the verb ('Lists'), resource ('Google Docs'), and scope ('within a specific Drive folder'). However, it doesn't distinguish this tool from sibling 'list_drive_items' or 'search_docs', which appear to have overlapping functionality, preventing 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.
Usage Guidelines2/5
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. There are multiple sibling tools like 'list_drive_items', 'search_docs', and 'search_drive_files' that might serve similar purposes, but the description offers no comparison or context for choosing this specific tool. The only implicit guidance is the folder-specific focus, but this isn't explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 the tool lists labels but doesn't describe important behaviors like whether it requires authentication, how it handles errors, if there are rate limits, or what happens with large numbers of labels. For a read operation 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the main purpose stated clearly in the first sentence. The Args and Returns sections add necessary structure without redundancy. It could be slightly more concise by integrating the parameter explanation into the main description, but overall it's efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter) and the presence of an output schema (which explains the return format), the description is somewhat complete. However, it lacks behavioral details like authentication needs or error handling, and with no annotations, it doesn't fully compensate for these gaps, making it only adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 adds meaning by explaining that 'user_google_email' is 'The user's Google email address' and is required, which clarifies the parameter's purpose beyond the schema's title. However, it doesn't provide details like format examples or constraints, keeping it at a baseline level.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('Lists') and resource ('all labels in the user's Gmail account'), making it easy to understand what it does. However, it doesn't explicitly distinguish itself from sibling tools like 'manage_gmail_label' or 'search_gmail_messages', 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.
Usage Guidelines2/5
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. There are multiple sibling tools related to Gmail (e.g., 'search_gmail_messages', 'manage_gmail_label'), but the description doesn't mention any context, prerequisites, or exclusions for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 the tool lists spreadsheets 'the user has access to,' which implies permission-based filtering, but doesn't disclose other behavioral traits like whether it requires authentication, has rate limits, pagination behavior, error conditions, or what happens if no spreadsheets are found. For a listing 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.
Conciseness4/5
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, then provides parameter documentation in a clear 'Args' section, and concludes with return information. Every sentence serves a purpose - no wasted words. The only minor improvement would be integrating the parameter information more seamlessly rather than as separate sections.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 (implied by 'Returns' section), the description doesn't need to explain return values in detail. However, for a listing tool with no annotations and 0% schema coverage, the description should do more to explain behavioral aspects like authentication requirements, error handling, or pagination. The parameter documentation helps, but overall completeness is adequate but with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The description compensates by documenting both parameters in the 'Args' section with types and purposes. However, it doesn't add meaning beyond basic documentation - no examples, constraints (e.g., email format validation, max_results range), or relationship between parameters. This meets the baseline for having parameter information but doesn't provide rich semantic context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Lists spreadsheets from Google Drive that the user has access to.' This is a specific verb ('Lists') + resource ('spreadsheets from Google Drive') with scope ('that the user has access to'). However, it doesn't explicitly differentiate from sibling tools like 'list_drive_items' or 'search_drive_files', 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.
Usage Guidelines2/5
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_drive_items' and 'search_drive_files' available, there's no indication of when this spreadsheet-specific listing tool is preferred over more general file listing or search tools. The description only states what it 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the basic action without disclosing key behavioral traits. It doesn't mention whether this is a read-only operation (implied but not explicit), potential rate limits, authentication needs, error conditions, or how comments are returned (e.g., format, pagination). 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words, making it easy to parse quickly. It front-loads the core purpose ('Read all comments') and specifies the resource without unnecessary elaboration, achieving optimal conciseness for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (2 required parameters) and the presence of an output schema (which should cover return values), the description is minimally adequate but incomplete. It lacks context on authentication, error handling, and parameter semantics, which are crucial for effective use despite the output schema handling return structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter details beyond names and types. The description adds no information about the parameters, such as what 'document_id' refers to (e.g., Google Docs ID format) or why 'user_google_email' is required (e.g., for authentication or filtering). This fails to compensate for the low schema coverage, leaving parameters poorly understood.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Read all comments') and resource ('from a Google Document'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'read_presentation_comments' or 'read_spreadsheet_comments' beyond specifying the document type, missing an opportunity to highlight unique scope or behavior.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_doc_content' (which might include comments) or other comment-reading tools for different Google Workspace apps. It lacks context about prerequisites, such as needing document access or when batch operations are preferable, leaving usage decisions ambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 it's a read operation, implying it's non-destructive, but doesn't disclose any behavioral traits like authentication requirements, rate limits, pagination, error conditions, or what the output contains. The description is minimal and lacks necessary context for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It's front-loaded with the core purpose and efficiently communicates the essential action. Every word earns its place in this concise statement.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 should document return values), the description's minimalism is somewhat acceptable. However, with no annotations and 0% schema description coverage, the description should do more to explain parameter usage and behavioral context. It's borderline adequate but leaves significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The description mentions 'Google Presentation' which hints at 'presentation_id', but doesn't explain what 'user_google_email' is for or how parameters interact. It adds minimal meaning beyond the bare schema, failing to compensate for the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Read') and resource ('all comments from a Google Presentation'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'read_document_comments' or 'read_spreadsheet_comments', but the specificity about 'Google Presentation' provides some distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. There are sibling tools for reading comments on documents and spreadsheets, but no indication of which to choose for different file types or scenarios. No prerequisites or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 reads comments but doesn't specify aspects like authentication requirements, rate limits, error handling, or the format of returned data (e.g., pagination, structure). 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every part of the sentence contributes essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (2 parameters) and the presence of an output schema (which handles return values), the description covers the basic purpose adequately. However, the lack of annotations and parameter details means it doesn't fully prepare the agent for practical use, such as understanding authentication or input formats.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides no information about the two required parameters ('spreadsheet_id' and 'user_google_email'), and the schema description coverage is 0%. This means the agent must rely solely on parameter names to infer meaning, which is insufficient for effective tool invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Read all comments') and resource ('from a Google Spreadsheet'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'read_document_comments' or 'read_presentation_comments', but the specificity about spreadsheet comments is adequate for clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, context for usage, or comparisons to similar tools like 'get_spreadsheet_info' or 'read_sheet_values', leaving the agent to infer usage based on the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'Reply to' implies a write/mutation operation, it doesn't specify authentication requirements, permission levels needed, whether replies are editable/deletable, rate limits, or what the response contains. The description is minimal and lacks crucial behavioral context for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized for the tool's apparent complexity and gets straight to the point without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists (which should document return values), the description's minimalism is somewhat acceptable. However, for a mutation tool with 4 parameters and no annotations, the description should provide more context about behavioral expectations and parameter meanings to be truly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage for all 4 parameters, the description provides no additional semantic information about what 'comment_id', 'document_id', 'reply_content', or 'user_google_email' represent, their formats, constraints, or relationships. The description fails to compensate for the complete lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Reply to') and target ('a specific comment in a Google Document'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'reply_to_presentation_comment' or 'reply_to_spreadsheet_comment' beyond specifying 'Google Document' in the description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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_document_comment' or 'resolve_document_comment'. There's no mention of prerequisites, context requirements, or exclusions, leaving the agent with minimal usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 ('Reply to') which implies a write operation, but doesn't mention permissions required, whether replies are editable/deletable, rate limits, or what the output contains. This leaves significant gaps for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that gets straight to the point with no wasted words. It's appropriately sized for a straightforward tool and is front-loaded with the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While an output schema exists (which helps), the description is inadequate for a 4-parameter mutation tool with no annotations. It doesn't explain parameter meanings, usage context, or behavioral aspects like authentication needs or side effects. The existence of an output schema prevents a lower score, but significant gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so all 4 parameters are undocumented in the schema. The description doesn't explain what 'comment_id', 'reply_content', 'spreadsheet_id', or 'user_google_email' represent or how to obtain them. It fails to compensate for the complete lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Reply to') and target resource ('a specific comment in a Google Spreadsheet'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'reply_to_document_comment' or 'reply_to_presentation_comment' beyond specifying 'Google Spreadsheet' as the context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'resolve_spreadsheet_comment' or 'create_spreadsheet_comment'. The description lacks any context about prerequisites, such as needing an existing comment to reply to, or when this operation is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It states the tool updates headers/footers and returns a confirmation message, but lacks critical details: it doesn't mention whether this is a destructive operation (e.g., overwrites existing content), if it requires specific permissions or authentication beyond the user email, or any rate limits. 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized: a clear purpose statement followed by 'Args' and 'Returns' sections. Each sentence earns its place by defining the tool and explaining parameters. It could be slightly more front-loaded by integrating key details into the opening, but overall it's efficient with minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 parameters, mutation operation) and lack of annotations, the description is moderately complete. It covers the purpose, parameters, and return value (with an output schema present, so return details aren't needed). However, it misses behavioral aspects like permissions or side effects, and parameter explanations are basic. For a mutation tool without annotations, this leaves gaps in contextual understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 lists all 5 parameters in the 'Args' section with brief explanations (e.g., 'Text content for the header/footer'), adding meaning beyond the bare schema. However, it doesn't elaborate on constraints (e.g., format of document_id, allowed values for section_type beyond 'header' or 'footer'), leaving some ambiguity. This partial compensation justifies a baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Updates headers or footers in a Google Doc.' It specifies the verb ('Updates') and resource ('headers or footers in a Google Doc'), making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'batch_update_doc' or 'modify_doc_text', which could also modify document 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.
Usage Guidelines2/5
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., user authentication, document permissions), compare it to siblings like 'batch_update_doc' for bulk operations, or specify scenarios where it's appropriate (e.g., formatting vs. content updates). This lack of context leaves the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'Update' implies a mutation operation, the description doesn't specify required permissions, whether changes are reversible, what happens to existing tasks in the list, or any rate limits. The confirmation message mentioned in Returns is helpful but insufficient 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (description, Args, Returns) and uses minimal sentences. Each section earns its place by providing essential information. The front-loaded purpose statement is effective, though the Args section could be more integrated rather than separate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with 3 parameters, 0% schema coverage, and no annotations, the description provides basic but incomplete coverage. The Args section helps, and the Returns section mentions output format, but critical behavioral aspects (permissions, side effects, error conditions) are missing. The existence of an output schema reduces but doesn't eliminate the need for more operational context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The description's Args section adds meaningful context by explaining each parameter's purpose, which compensates somewhat for the schema gap. However, it doesn't provide format details (like email validation or ID format examples) or explain why user_google_email is required for an update operation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 task list'), making the purpose immediately understandable. It distinguishes itself from sibling tools like 'create_task_list' by specifying it updates existing lists rather than creating new ones. However, it doesn't explicitly differentiate from 'update_task' which modifies individual tasks rather than task lists.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 existing task list ID), doesn't specify when to choose this over creating a new task list, and doesn't reference sibling tools like 'update_task' for modifying individual tasks. The agent must infer usage context 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.
Behavior2/5
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 tasks will be 'marked as hidden' rather than permanently deleted, which is useful behavioral context. However, it doesn't mention authentication requirements, rate limits, whether the action is reversible, or what happens if no completed tasks exist. For a mutation 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections for purpose, arguments, and return value. It's appropriately sized at three sentences plus structured parameter documentation. Every sentence adds value, though the 'Args' and 'Returns' sections could be integrated more seamlessly into the narrative flow.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, mutation operation) and the presence of an output schema (which handles return value documentation), the description is reasonably complete. It covers the core purpose, parameters, and behavioral effect ('marked as hidden'). The main gap is lack of usage guidance relative to sibling tools, but otherwise it provides sufficient context for basic understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The description includes an 'Args' section that documents both parameters with brief explanations, adding meaningful semantics beyond the bare schema. However, it doesn't specify format requirements (e.g., email validation) or where to find the task_list_id, leaving some gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('clear all completed tasks') and resource ('from a task list'), with the specific effect that tasks will be marked as hidden. However, it doesn't explicitly differentiate this tool from sibling tools like 'delete_task' or 'delete_task_list', which handle different types of task-related operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'delete_task' (for individual tasks) and 'delete_task_list' (for entire lists), there's no indication of when clearing completed tasks is preferred over deletion or other task management operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 creates a spreadsheet, implying a write/mutation operation, but doesn't cover critical aspects like required permissions (e.g., Google Drive access), rate limits, error conditions, or whether the operation is idempotent. The return value is mentioned but lacks detail on format or potential errors.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized. It front-loads the core purpose in the first sentence, followed by clear sections for Args and Returns. Each sentence adds value, with no redundant or vague phrasing. Minor improvements could include integrating the sections more seamlessly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a write operation with 3 parameters, no annotations, but an output schema exists), the description is partially complete. It covers parameters well and mentions the return value, but lacks behavioral context (e.g., auth, errors) and usage guidelines. The output schema reduces the need to detail return values, but other gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 meaningful semantics for all three parameters: 'user_google_email' is explained as 'The user's Google email address', 'title' as 'The title of the new spreadsheet', and 'sheet_names' with details on default behavior and optionality. This clarifies beyond the bare schema, though it doesn't cover validation rules (e.g., email format).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Creates a new Google Spreadsheet.' It specifies the verb ('Creates') and resource ('Google Spreadsheet'), making the action unambiguous. However, it doesn't differentiate from sibling tools like 'create_doc' or 'create_sheet', which are similar creation tools for different Google Workspace resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 needs), compare it to similar tools like 'create_sheet' (which might create a single sheet versus a full spreadsheet), or specify use cases. The agent must 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.
Behavior2/5
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 the action ('Deletes') and return value, but lacks critical behavioral details: required permissions, whether deletion is permanent/reversible, error conditions (e.g., invalid event_id), or side effects. For a destructive operation with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose. The 'Args' and 'Returns' sections are organized efficiently, with no redundant sentences. Every part adds value, making it appropriately concise for a tool with three parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a destructive tool with no annotations, 0% schema coverage, but an output schema (implied by 'Returns'), the description is minimally adequate. It covers parameters and return value, but lacks behavioral context (permissions, irreversibility) and usage guidelines. The output schema reduces the need to explain returns, but gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates by documenting all three parameters in the 'Args' section, including data types and the default for 'calendar_id'. However, it doesn't explain parameter semantics beyond basic definitions (e.g., what constitutes a valid 'event_id', format of 'user_google_email'). The baseline is 3 due to partial compensation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Deletes') and resource ('an existing event'), making the purpose unambiguous. It distinguishes itself from sibling tools like 'modify_event' by specifying deletion rather than modification. However, it doesn't explicitly contrast with other deletion tools (e.g., 'delete_task'), though those target different resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 proper permissions), exclusions (e.g., cannot delete recurring events), or comparisons to sibling tools like 'modify_event' for updates. 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden of behavioral disclosure. While it mentions the action and return format, it doesn't address important behavioral aspects: whether this requires specific permissions, if changes are reversible, whether it affects document history/versioning, or if there are rate limits. For a mutation tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, Args, Returns) and uses minimal words to convey essential information. The front-loaded purpose statement is effective, though the Args section could be slightly more concise by integrating some details into the main description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with 5 parameters, 0% schema description coverage, and no annotations, the description does an adequate job covering the basics. The presence of an output schema reduces the need to explain return values in the description. However, given the tool's complexity (text replacement in documents), more behavioral context about permissions, side effects, and limitations would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description provides valuable parameter context through the Args section. It clearly explains what each parameter represents (user's Google email, document ID, text to search for, etc.) and adds the 'match_case' default behavior. This compensates well for the schema's lack of descriptions, though it doesn't provide format examples or validation rules.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Finds and replaces text') and resource ('throughout a Google Doc'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'modify_doc_text' or 'batch_update_doc', which could 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.
Usage Guidelines2/5
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 multiple document modification tools in the sibling list (modify_doc_text, batch_update_doc, insert_doc_elements), there's no indication of when this specific find-and-replace operation is appropriate versus other document editing approaches.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. While 'Get details' implies a read-only operation, it doesn't disclose behavioral traits like authentication requirements, rate limits, error conditions, or whether the operation is idempotent. The description adds minimal context beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (Args, Returns) and front-loaded with the core purpose. Every sentence adds value: the first states the purpose, Args explains parameters, Returns describes output. It's appropriately sized without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 required parameters, no annotations, but has output schema), the description is partially complete. It covers purpose and parameters adequately, and the output schema exists (so return values needn't be detailed). However, for a tool with zero annotation coverage, it lacks behavioral context like permissions or error handling, leaving gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates by explaining both parameters in the Args section: 'user_google_email' is described as 'The user's Google email address' and 'task_list_id' as 'The ID of the task list to retrieve'. This adds meaningful semantics beyond the schema's bare titles. However, it doesn't specify format constraints (e.g., email validation, ID format).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('a specific task list'), making the purpose unambiguous. It distinguishes from sibling tools like 'list_task_lists' (which lists multiple) by specifying retrieval of a single task list. However, it doesn't explicitly differentiate from 'get_task' (which retrieves individual tasks rather than lists).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'list_task_lists' (for listing all task lists) or 'get_task' (for retrieving individual tasks), nor does it specify prerequisites or contextual constraints for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 it implies a write/mutation operation ('inserts'), it doesn't address important behavioral aspects like required permissions, whether the operation is idempotent, error conditions, or rate limits. The description mentions what the tool does but not how it behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose statement followed by organized sections for Args and Returns. Each sentence serves a specific purpose without redundancy. The only minor improvement would be integrating the parameter explanations more seamlessly rather than as a separate bulleted list.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with 8 parameters and no annotations, the description does a good job explaining parameters and return values. However, it lacks important contextual information about authentication requirements (though user_google_email suggests Google auth), error handling, or behavioral constraints. The presence of an output schema helps, but more behavioral context would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description provides excellent parameter clarification beyond the bare schema. It explains conditional requirements (rows/columns 'required for table', list_type 'required for list'), clarifies the index as '0-based', and provides enum values for element_type and list_type. This significantly compensates for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('inserts') and target resources ('structural elements like tables, lists, or page breaks into a Google Doc'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'insert_doc_image' or 'modify_doc_text', which handle different types of document modifications.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 many sibling tools for document manipulation (e.g., 'insert_doc_image', 'modify_doc_text', 'find_and_replace_doc'), there's no indication of when this specific insertion tool is appropriate versus other document editing tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'accessible to the authenticated user', which hints at permission requirements, but lacks details on rate limits, pagination, error handling, or what 'formatted list' entails. For a read operation with zero annotation coverage, this is insufficient behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose. The 'Args' and 'Returns' sections are clear but slightly redundant since an output schema exists. Every sentence adds value, though it could be more concise by omitting the return statement given the output schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 1 parameter with 0% schema coverage and an output schema, the description is minimally adequate. It covers the parameter's purpose and return format, but lacks behavioral context like authentication needs or error cases. With annotations absent and simple complexity, it meets baseline but doesn't excel.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 meaning by explaining that 'user_google_email' is 'The user's Google email address' and is 'Required', which clarifies beyond the schema's basic title. However, it doesn't detail format constraints or examples, leaving some gaps. With 1 parameter and partial compensation, a 4 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Retrieves a list of calendars accessible to the authenticated user.' It specifies the verb ('retrieves') and resource ('calendars'), and distinguishes from siblings like 'get_events' or 'list_task_lists' by focusing on calendars. However, it doesn't explicitly differentiate from potential calendar-related siblings not present in the list, 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.
Usage Guidelines2/5
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 status), compare to other list tools like 'list_drive_items', or specify scenarios where this is appropriate. The only implied usage is for retrieving calendars, but no explicit when/when-not instructions are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 pagination ('pagination info') and implies read-only behavior through 'List', but lacks critical details: authentication requirements (Google email suggests OAuth), rate limits, error conditions, or what 'basic details' includes. For a tool with 4 parameters and no 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (Args, Returns) and front-loads the core purpose. Each sentence adds value, but the 'Returns' section could be more specific about output format given the output schema exists, making it slightly redundant.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters, 0% schema coverage, no annotations, and an output schema, the description is moderately complete. It covers parameter meanings and hints at pagination, but lacks behavioral context (e.g., auth, errors) and doesn't leverage the output schema to avoid repeating return details. For a list operation with pagination, more guidance on usage and limits would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 meaningful context for all parameters: 'user_google_email' is explained as 'The user's Google email address. Required.', 'form_id' as 'The ID of the form.', and pagination parameters with defaults and purposes. This goes beyond the bare schema, though it could elaborate on format constraints (e.g., email validation).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 'a form's responses', making the purpose immediately understandable. It distinguishes from sibling tools like 'get_form' or 'get_form_response' by focusing on listing multiple responses rather than retrieving a single form or response. However, it doesn't explicitly differentiate from other list tools like 'list_docs_in_folder' or 'list_tasks', which keeps it from 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.
Usage Guidelines2/5
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 form access), compare to similar tools (e.g., 'get_form_response' for single responses), or specify use cases. 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.
Behavior2/5
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 pagination via page_token and a max_results default/max, which is useful. However, it doesn't disclose critical behavioral traits: whether this is a read-only operation (implied but not stated), if it requires specific Google API permissions, rate limits, error conditions, or how the returned data is structured beyond the vague 'List of task lists with their IDs, titles, and details.'
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose. The Args and Returns sections are clear and organized. However, the Returns section could be more precise (e.g., specifying JSON structure instead of 'str'), and there's some redundancy in stating 'List all task lists' then 'List of task lists' in Returns.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters with 0% schema coverage and no annotations, the description does a decent job explaining parameters and implying read-only behavior. However, it lacks output schema details (though one exists, the description doesn't leverage it), and omits authentication, error handling, and sibling tool differentiation. For a list tool with user-specific scope, this is minimally adequate but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 provides meaningful context for all three parameters: user_google_email is explained as 'The user's Google email address. Required.', max_results specifies default and max values, and page_token clarifies its purpose for pagination. This adds significant value beyond the bare schema, though it could elaborate on format (e.g., email validation) or token usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 task lists for the user.' It specifies the verb ('List') and resource ('task lists'), and includes scope ('for the user'). However, it doesn't explicitly differentiate from sibling tools like 'get_task_list' (which retrieves a single task list) or 'list_tasks' (which lists tasks within a list).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_task_list' for retrieving a specific task list or 'create_task_list' for creating new ones. There's no context about prerequisites, such as authentication or user permissions, which is a significant gap given the required user_google_email parameter.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 the tool performs create/update/delete operations (implying mutations) and mentions what parameters are required for which actions, but doesn't disclose important behavioral traits like authentication requirements, error conditions, whether operations are reversible, rate limits, or what happens to existing messages when labels are deleted. For a mutation 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized. It begins with a clear purpose statement, then provides organized parameter explanations in an 'Args:' section, and concludes with return information. Every sentence earns its place, though the 'Returns:' section could be slightly more informative beyond just 'confirmation message'.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 6 parameters, 0% schema description coverage, no annotations, but with an output schema, the description is moderately complete. It explains parameters well and mentions the return type, but lacks important context about authentication, error handling, and behavioral constraints. The presence of an output schema helps, but doesn't compensate for missing mutation-related disclosures.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides excellent parameter semantics beyond the schema. With 0% schema description coverage, the description fully compensates by explaining: 1) which parameters are required for which actions, 2) the meaning of visibility parameters ('label_list_visibility' and 'message_list_visibility'), and 3) the purpose of each parameter. This adds substantial value over the bare schema which only shows titles and types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Manages Gmail labels: create, update, or delete labels.' This specifies the verb ('manages') and resource ('Gmail labels') with the three specific actions. However, it doesn't distinguish this tool from sibling tools like 'modify_gmail_message_labels' or 'list_gmail_labels' which also handle Gmail labels in different ways.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. There's no mention of prerequisites, when to choose create vs update vs delete, or how this differs from sibling tools like 'modify_gmail_message_labels' or 'list_gmail_labels'. The agent must infer usage from the action parameter alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 this is an update operation, implying mutation, but doesn't cover critical aspects like required permissions, whether changes are reversible, rate limits, or error conditions. The description adds minimal behavioral context 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose statement followed by organized Args and Returns sections. It's appropriately sized without unnecessary fluff, though the Args section is somewhat detailed, which is acceptable given the parameter complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the mutation nature, lack of annotations, and 4 parameters, the description is moderately complete. It covers parameters and return value, but lacks behavioral details like permissions or side effects. The output schema exists, so describing return values isn't needed, but overall coverage is adequate with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 documenting all 4 parameters in the Args section, including their types, purposes, and defaults. This adds significant meaning beyond the bare schema, though it doesn't fully explain edge cases or validation rules.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Updates the publish settings of a form.' It specifies the verb ('Updates') and resource ('publish settings of a form'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'create_form' or 'get_form', which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 form), exclusions, or compare it to related tools like 'create_form' or 'get_form'. This lack of context leaves the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 performs label modifications but doesn't mention authentication requirements, rate limits, error handling, or whether changes are reversible. For a mutation 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose, followed by parameter and return details. It's appropriately sized with no redundant sentences, though the parameter explanations could be slightly more concise by integrating them into the main description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (batch mutation with 4 parameters), no annotations, and an output schema that only indicates a string return, the description is moderately complete. It covers the basic operation and parameters but lacks details on permissions, error cases, and practical usage context, which are important for a mutation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50% (two of four parameters have descriptions). The description adds value by clarifying that 'add_label_ids' and 'remove_label_ids' are optional and operate on lists, but doesn't explain parameter interactions (e.g., what happens if the same label is in both lists) or provide examples. It partially compensates for the schema gap but not fully.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Adds or removes labels from multiple Gmail messages') and resource ('Gmail messages'), distinguishing it from sibling tools like 'modify_gmail_message_labels' by emphasizing batch processing. The verb+resource combination is precise and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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_gmail_message_labels' (which appears to handle single messages). The description mentions batch processing but doesn't explicitly advise on scenarios where batch is preferred over individual modifications or vice versa.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'creates' (implying a write/mutation operation) and returns a confirmation message, but lacks details on permissions required (e.g., edit access to the spreadsheet), error conditions (e.g., invalid spreadsheet ID), rate limits, or whether the operation is idempotent. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded: the first sentence states the purpose clearly, followed by organized sections for arguments and returns. Every sentence earns its place—no fluff or redundancy. It's appropriately sized for a tool with three parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, mutation operation), no annotations, and an output schema (implied by 'Returns' section), the description is partially complete. It covers the purpose and parameters well but lacks behavioral context (e.g., permissions, errors) and doesn't fully explain the return value beyond 'confirmation message' (though the output schema might detail this). For a mutation tool, more disclosure is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes an 'Args' section that documents all three parameters with names and types, adding significant value beyond the input schema (which has 0% description coverage). It clarifies that 'user_google_email' is the user's Google email, 'spreadsheet_id' is the ID of the spreadsheet, and 'sheet_name' is the name of the new sheet, all required. This compensates well for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Creates a new sheet within an existing spreadsheet.' It specifies the verb ('creates'), resource ('new sheet'), and context ('within an existing spreadsheet'). However, it doesn't explicitly differentiate from sibling tools like 'create_spreadsheet' (which creates entire spreadsheets) or 'modify_sheet_values' (which modifies existing sheets), though the context implies it's for adding sheets to existing spreadsheets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 spreadsheet), exclusions, or comparisons to sibling tools like 'create_spreadsheet' (for new spreadsheets) or 'modify_sheet_values' (for editing sheets). The agent must infer usage from the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 operation (implying mutation) and mentions a return confirmation, but lacks critical details: required permissions, whether this affects existing data, error conditions, or rate limits. For a mutation 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly structured and concise: a clear purpose statement followed by well-organized Args and Returns sections. Every sentence earns its place, with no redundant information. The front-loaded purpose makes it immediately scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a mutation tool with no annotations but with an output schema (implied by 'Returns' section), the description is moderately complete. It covers parameters well and indicates return format, but lacks behavioral context about permissions, side effects, or error handling. The presence of an output schema reduces the need to describe return values, but other gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explicitly documents both parameters in the Args section, adding meaning beyond the schema which has 0% description coverage. It clarifies that user_google_email is 'required' and identifies it as the user's Google email, and explains title is for the new task list. This fully compensates for the schema's lack of descriptions, though it doesn't provide format examples or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 'task list', making the purpose immediately understandable. It distinguishes this from sibling tools like 'create_task' (which creates individual tasks) and 'create_task_list' (which creates lists). However, it doesn't explicitly contrast with 'update_task_list' or 'delete_task_list', keeping it from 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.
Usage Guidelines2/5
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 existing user account), when not to use it, or how it differs from related tools like 'update_task_list' or 'list_task_lists'. The agent must 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.
Behavior2/5
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 the action is 'Delete' which implies a destructive mutation, but doesn't specify whether deletion is permanent/reversible, what permissions are required, or if there are rate limits. The confirmation message return is mentioned but not elaborated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by well-organized parameter and return value sections. Every sentence serves a purpose with no redundant information, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive mutation tool with no annotations, the description provides basic purpose and parameter documentation, and mentions a return value. However, it lacks important context about permissions, side effects, and error conditions that would be crucial for safe usage. The output schema exists but isn't detailed in the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description provides clear parameter documentation in the Args section, explaining what each parameter represents (user email, task list ID, task ID) and which are required. This compensates well for the schema's lack of descriptions, though it doesn't provide format examples or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Delete') and target resource ('a task from a task list'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'delete_task_list' or 'clear_completed_tasks', which would require more specific context about scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, permissions needed, or differences from similar deletion tools like 'delete_task_list' or 'clear_completed_tasks' (which might handle bulk operations).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 indicates this is a read operation ('Gets'), which implies it's non-destructive, but doesn't specify authentication requirements, rate limits, error conditions, or what 'detailed metadata' entails beyond permissions. The description adds some context (it returns sharing status and URLs) but lacks comprehensive behavioral details for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized. It starts with a clear purpose statement, followed by an 'Args' section that explains parameters concisely, and a 'Returns' section that summarizes the output. There's no wasted text, and information is front-loaded, though the bullet-point style is slightly less efficient than a single flowing paragraph.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, no annotations, but has an output schema), the description is reasonably complete. It explains what the tool does, the parameters, and the return value. The presence of an output schema means the description doesn't need to detail return values extensively. However, it could improve by addressing behavioral aspects like authentication or error handling, given the lack of annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, meaning parameters are undocumented in the schema. The description adds value by explaining that 'user_google_email' is 'The user's Google email address' and 'file_id' is 'The ID of the file to check permissions for', which clarifies their roles. However, it doesn't provide format details (e.g., email validation, file ID structure) or examples, leaving some ambiguity. With 2 parameters and no schema documentation, this is adequate but not thorough.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Gets detailed metadata about a Google Drive file including sharing permissions.' It specifies the verb ('Gets'), resource ('Google Drive file'), and scope ('including sharing permissions'). However, it doesn't explicitly differentiate from sibling tools like 'check_drive_file_public_access' or 'get_drive_file_content', which is why it doesn't 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.
Usage Guidelines2/5
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 'check_drive_file_public_access' (which might check public access specifically) or 'get_drive_file_content' (which retrieves file content rather than permissions), nor does it specify prerequisites or exclusions. This leaves the agent with minimal 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.
Behavior2/5
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 read operation ('Get'), but doesn't mention authentication requirements, permission levels needed, rate limits, error conditions, or what happens if the response doesn't exist. For a tool that accesses potentially sensitive form response data, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by well-organized sections for Args and Returns. Every sentence serves a distinct purpose with zero wasted words, making it easy to scan and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read operation with 3 parameters and an output schema, the description covers the basic purpose and parameters adequately. However, without annotations and with sensitive data access (form responses), it should provide more behavioral context about authentication, permissions, and error handling. The existence of an output schema reduces the need to describe return values, but the description could better address the tool's operational context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides meaningful context for all three parameters in the 'Args' section, explaining what each parameter represents (user's Google email, form ID, response ID). With 0% schema description coverage, this documentation is essential and adds substantial value beyond the bare schema. The only minor gap is not explaining why user_google_email is required.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('one response from the form'), making it immediately understandable. It distinguishes itself from sibling 'list_form_responses' by focusing on retrieving a single specific response rather than listing multiple responses.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. While it implicitly contrasts with 'list_form_responses' by retrieving a single response, there's no explicit mention of when to choose this over batch operations or other form-related tools, nor any prerequisites or constraints for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 the tool retrieves metadata but doesn't describe what 'metadata' includes beyond 'configuration and available refinements.' It omits critical behavioral details: whether this requires specific permissions, rate limits, authentication scope, error conditions, or what format the returned information takes. The description provides minimal behavioral context beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by separate Args and Returns sections. Every sentence adds value: the first states the operation, the second explains the parameter, and the third describes the return. There's no wasted text, and information is front-loaded appropriately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (metadata retrieval with authentication), no annotations, and an output schema exists (though not shown), the description is minimally adequate. It covers the basic operation and parameter but lacks behavioral context about permissions, rate limits, or error handling. The existence of an output schema means the description doesn't need to detail return values, but it should provide more operational context for a tool requiring user authentication.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context for the single parameter. The schema has 0% description coverage (just 'User Google Email'), while the description explains it's 'The user's Google email address' and 'Required.' This clarifies the parameter's purpose and requirement status beyond the bare schema. For a single parameter tool, this provides adequate semantic value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('Retrieves') and resource ('metadata about a Programmable Search Engine'). It distinguishes itself from sibling tools by focusing on search engine metadata rather than document, email, or task operations. However, it doesn't explicitly differentiate from potential similar metadata retrieval tools (though none appear in the sibling list).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. While the sibling list shows no direct alternatives for search engine metadata, there's no mention of prerequisites, context, or comparison with other information retrieval tools like get_spreadsheet_info or get_form. The agent receives no usage context beyond the basic purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 read operation but doesn't mention authentication requirements (beyond the user_google_email parameter), rate limits, error conditions, or what happens with invalid ranges. The return type is mentioned but without format details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear opening sentence followed by organized sections for Args and Returns. Every sentence adds value, and there's no redundant information. The formatting makes it easy to scan and understand.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, read operation) and the presence of an output schema (though not shown here), the description covers the basics adequately. However, with no annotations and incomplete behavioral context, it leaves gaps about authentication flow, error handling, and practical usage scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant value beyond the schema, which has 0% description coverage. It explains what each parameter represents (e.g., 'range_name' examples like 'Sheet1!A1:D10'), clarifies defaults, and distinguishes required vs. optional parameters. This compensates well for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Reads values') and resource ('from a specific range in a Google Sheet'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_spreadsheet_info' or 'modify_sheet_values', 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.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_spreadsheet_info' or 'list_spreadsheets'. It mentions required parameters but offers no context about prerequisites, permissions, 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.
Behavior2/5
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 'Update' implies mutation, the description doesn't mention permission requirements, whether changes are reversible, error conditions, or rate limits. The return format is mentioned but lacks detail about what happens on partial updates or conflicts.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (Args, Returns) and uses bullet-like formatting. While efficient, the opening statement 'Update an existing task' is somewhat redundant with the tool name, and the parameter explanations could be slightly more concise while maintaining clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with 7 parameters and no annotations, the description does well on parameters but lacks behavioral context. The output schema exists, so return values don't need explanation, but important operational details like authentication requirements, error handling, and side effects are missing, making it incomplete for safe agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description provides excellent parameter documentation. It clearly explains all 7 parameters, their types, which are required, optional values, and even includes format specifications (RFC 3339 format for 'due') and enum values for 'status'. This fully compensates for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 task'), providing specific verb+resource pairing. However, it doesn't differentiate from sibling tools like 'modify_event' or 'update_task_list', 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.
Usage Guidelines2/5
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. There are multiple sibling tools that modify data (modify_event, modify_gmail_message_labels, update_task_list), but the description offers no comparison or context about appropriate use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but lacks critical behavioral details. It doesn't disclose whether this requires specific permissions, how it handles multiple matching files, error conditions, or rate limits. The description mentions the return format but doesn't explain the search behavior or limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections for purpose, arguments, and returns. It's appropriately sized with no redundant information, though the return statement could be more specific about the exact format of the information returned.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 2 parameters, no annotations, and an output schema, the description adequately covers the basic purpose and parameters but lacks behavioral context. The presence of an output schema means the description doesn't need to detail return values, but it should provide more operational guidance given the mutation-adjacent nature of checking sharing status.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explicitly lists both parameters with their purposes in the Args section, adding meaningful context beyond the schema which has 0% description coverage. It clarifies that 'user_google_email' is required and identifies the file to check, though it doesn't specify format constraints or search behavior details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('searches for a file by name and checks if it has public link sharing enabled'), identifies the resource (file), and distinguishes it from sibling tools like 'search_drive_files' or 'get_drive_file_permissions' by focusing on public access checking rather than general search or permission listing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_drive_file_permissions' or 'search_drive_files'. It doesn't mention prerequisites, exclusions, or specific scenarios where this tool is preferred over others for checking public access.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but provides minimal behavioral information. It states this is a creation operation but doesn't mention permissions needed (beyond the email parameter), rate limits, whether this requires authentication, or what happens on failure. The return format is mentioned but lacks detail about error conditions or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by Args and Returns sections. Every sentence serves a purpose, though the 'Returns' section could be more specific about what 'Details' includes. The formatting helps readability but isn't perfectly front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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, 2 parameters, and an output schema, the description is minimally adequate. It covers the basic purpose and parameters but lacks important context about authentication, error handling, and when to choose this over other creation tools. The presence of an output schema reduces the need to describe return values in detail.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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: user_google_email is described as 'The user's Google email address. Required.' and title as 'The title for the new presentation. Defaults to "Untitled Presentation".' This adds meaningful context beyond the bare schema, though it doesn't explain format constraints or validation rules.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 Google Slides presentation') and resource ('presentation'), distinguishing it from sibling tools like create_doc or create_spreadsheet. It uses precise language that leaves no ambiguity about what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 create_doc or create_spreadsheet. The description doesn't mention prerequisites, use cases, or any context that would help an agent decide between this and other creation tools in the sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 generates a URL but doesn't clarify if this requires specific permissions (e.g., view access to the presentation), whether the URL is ephemeral or persistent, or any rate limits. For a tool with authentication parameters and no annotations, 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.
Conciseness4/5
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 followed by structured parameter and return details. Every sentence adds value, though the 'Args' and 'Returns' sections could be integrated more seamlessly. It avoids redundancy and is easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, no annotations, but with an output schema), the description is partially complete. It covers parameters well but lacks behavioral context (e.g., authentication needs, URL validity). The output schema exists, so the description doesn't need to detail return values, but overall it's adequate with clear gaps in usage and transparency.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds substantial meaning beyond the input schema, which has 0% description coverage. It explains each parameter's purpose: 'user_google_email' as the user's email, 'presentation_id' as the ID of the presentation, 'page_object_id' as the object ID of the page/slide, and 'thumbnail_size' with its enum values and default. This compensates well for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Generate a thumbnail URL') and resource ('for a specific page/slide in a presentation'), distinguishing it from siblings like 'get_presentation' or 'get_page' which retrieve content rather than generate visual representations. The verb 'generate' is precise and differentiates the tool's function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 access to the presentation), compare it to similar tools like 'get_page' (which might retrieve slide content without a thumbnail), or specify use cases (e.g., for previews or embedding). 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.
Behavior3/5
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 the tool retrieves information (a read operation) and specifies the return format ('Formatted spreadsheet information including title and sheets list'), which adds useful behavioral context. However, it doesn't disclose potential limitations like authentication requirements, rate limits, error conditions, or whether it requires specific permissions, leaving gaps for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with distinct sections for purpose, arguments, and returns, making it easy to parse. It's front-loaded with the core purpose. However, the 'Args' and 'Returns' sections are somewhat redundant with the input and output schemas, and the purpose sentence could be more concise (e.g., by integrating parameter hints).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, read-only operation), no annotations, and an output schema present, the description is reasonably complete. It covers purpose, parameters, and return format. The output schema means return values don't need explanation, but additional context like error handling or usage examples would enhance completeness for a tool with zero annotation coverage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 documents both parameters in the Args section with names, types, and required status, adding clear meaning beyond the bare schema. However, it doesn't explain parameter semantics (e.g., what constitutes a valid spreadsheet_id or how user_google_email is used), leaving some ambiguity. With 2 parameters fully listed but not fully explained, this is above baseline but not perfect.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Gets information about a specific spreadsheet including its sheets.' It specifies the verb ('Gets'), resource ('spreadsheet'), and scope ('including its sheets'), which distinguishes it from generic list operations. However, it doesn't explicitly differentiate from sibling tools like 'list_spreadsheets' or 'get_search_engine_info' beyond the specific resource focus.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'list_spreadsheets' (for listing spreadsheets) or 'read_sheet_values' (for reading content), nor does it specify prerequisites or appropriate contexts. The agent must infer usage from the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 an insertion operation but doesn't mention whether this requires specific permissions, if it's destructive to existing content, what happens if the index is invalid, or any rate limits. The return value is mentioned but not detailed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose statement followed by organized Args and Returns sections. Every sentence serves a purpose, though the Args section could be slightly more concise by integrating some details into the main description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with 8 parameters and no annotations, the description does a good job explaining parameters but lacks important behavioral context. The presence of an output schema helps with return values, but critical information about permissions, error conditions, and operational constraints is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description provides excellent parameter clarification beyond the bare schema. It explains what each parameter represents (e.g., 'Position to insert image (0-based)', 'Drive file ID or public image URL', 'Image width in points'), giving meaningful context that the schema titles lack.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Inserts an image') and target resource ('into a Google Doc'), with explicit sources ('from Drive or a URL'). It distinguishes itself from sibling tools like 'insert_doc_elements' or 'modify_doc_text' by focusing specifically on image insertion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'insert_doc_elements' or 'batch_update_doc'. It mentions the image sources but doesn't explain when to choose Drive vs URL, or prerequisites like authentication or permissions needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 discloses that the tool creates a new form and returns a confirmation message with form ID and edit URL, which is useful behavioral context. However, it lacks details on permissions (e.g., whether the user needs specific Google Forms access), error handling, or rate limits. The description doesn't contradict annotations (none provided), but it's incomplete for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and concise, with three clear sections: purpose statement, parameter details, and return value. Each sentence earns its place by providing essential information without redundancy. It's front-loaded with the main action and efficiently covers key aspects in minimal text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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 with 4 parameters), no annotations, and an output schema present (which covers return values), the description is reasonably complete. It explains the purpose, parameters, and return value, compensating for the lack of annotations. However, it could improve by adding more behavioral context (e.g., auth needs) and usage guidelines, making it slightly incomplete for optimal agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes an 'Args' section that lists all four parameters (user_google_email, title, description, document_title) with brief explanations, adding meaning beyond the input schema, which has 0% description coverage. It clarifies that user_google_email is required and distinguishes optional parameters. However, it doesn't provide examples, constraints, or format details (e.g., email validation), leaving some gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 a new form using the title given in the provided form message in the request.' It specifies the verb ('Create') and resource ('a new form'), making the action explicit. However, it doesn't differentiate from sibling tools like 'create_doc' or 'create_spreadsheet' beyond mentioning 'form', which is somewhat implied by the tool name itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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., Google Forms access), exclusions, or compare it to similar tools like 'create_doc' or 'create_spreadsheet'. The only implied context is creating forms, but no explicit usage instructions are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 the action ('exports', 'saves') but lacks critical behavioral details: required permissions (e.g., edit access to the Doc, write access to Drive), whether the original Doc is modified, error conditions (e.g., invalid IDs, quota limits), or response format beyond the return statement. The description is minimal beyond basic functionality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded: the first sentence states the core purpose, followed by organized sections for Args and Returns. Each sentence earns its place by explaining parameters and outcomes without redundancy, making it easy to scan and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, 4 parameters with 0% schema coverage, and an output schema (returns str), the description is moderately complete. It covers parameter semantics and return type but lacks behavioral context (e.g., permissions, errors) and doesn't fully compensate for the missing annotations, leaving gaps for a mutation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 meaningful context for all parameters: 'user_google_email' specifies the user's email, 'document_id' identifies the Doc, 'pdf_filename' explains naming rules (optional, default behavior), and 'folder_id' specifies save location (optional, defaults to root). This clarifies purpose beyond schema titles like 'Document Id'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Exports a Google Doc to PDF format') and the resource involved ('Google Doc'), then specifies the destination ('saves it to Google Drive'). It distinguishes from siblings like 'get_doc_content' (read-only) or 'create_doc' (creation) by focusing on format conversion and storage.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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., document accessibility, user permissions), compare to similar tools like 'get_drive_file_content' (which might retrieve files without conversion), or specify use cases (e.g., archiving, sharing).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 clearly indicates this is a destructive operation with cascading effects, which is valuable. However, it doesn't mention authentication requirements, error conditions, or whether the deletion is reversible, leaving some behavioral aspects unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, Args, Returns) and front-loads the most important information. The warning about cascading deletion is appropriately placed. It could be slightly more concise by integrating the warning more seamlessly, but overall it's efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive operation with no annotations, the description does a good job covering the essentials: purpose, parameters, return value, and critical behavioral warning. The output schema exists (Returns: str), so the description doesn't need to elaborate on return values. The main gap is lack of authentication/authorization context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explicitly documents both parameters with their types and requirements in the Args section, adding significant value beyond the schema (which has 0% description coverage). It clarifies that user_google_email is 'The user's Google email address' and task_list_id is 'The ID of the task list to delete', providing essential semantic context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Delete a task list') and specifies the resource ('task list'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'delete_task' or 'delete_event', 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.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes an important warning about cascading deletion ('This will also delete all tasks in the list'), which provides some usage context. However, it doesn't explicitly state when to use this versus alternatives like 'clear_completed_tasks' or provide prerequisites beyond the required parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses behavioral traits such as using different APIs (Docs API for native Google Docs, Drive API for Office files) and returning content with a metadata header, which adds context beyond basic retrieval. However, it misses details like rate limits, error handling, or permission requirements, which are important for a tool with multiple API integrations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, starting with the core purpose. It uses bullet points for clarity on file handling and a clear 'Returns' section. However, the bullet points could be more integrated, and some redundancy exists (e.g., repeating 'Drive' in contexts), but overall it's efficient with minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of handling multiple file types and APIs, the description is fairly complete. It explains the retrieval process and return format, and since an output schema exists, it doesn't need to detail return values. However, the lack of parameter explanations and some behavioral details (e.g., auth or errors) prevents a perfect score, but it's adequate for basic use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 mentions 'document_id' but does not explain the other three parameters ('docs_service', 'drive_service', 'user_google_email'), leaving their purposes unclear. This gap is significant given the 4 required parameters, reducing the tool's usability without additional context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Retrieves content'), the resource ('Google Doc or a Drive file'), and the identifier ('document_id'). It distinguishes from sibling tools like 'get_drive_file_content' by specifying it handles both native Google Docs and Office files, and from 'inspect_doc_structure' by focusing on content extraction rather than structural analysis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by specifying the types of files it handles (Google Docs and Office files like .docx), which helps differentiate it from tools like 'get_drive_file_content' that might handle other file types. However, it lacks explicit guidance on when to use alternatives (e.g., 'get_drive_file_content' for non-text files) or prerequisites like authentication needs, leaving some ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It adds some context: it describes pagination via 'page_token', default values (e.g., 'max_results: 20'), and interactions between parameters (e.g., 'show_hidden must also be true to show tasks completed in first party clients'). However, it doesn't cover critical aspects like authentication needs, rate limits, or error handling, which are important for a tool with 13 parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose statement followed by detailed parameter documentation. It's appropriately sized for a tool with many parameters, but some redundancy exists (e.g., repeating 'Optional[str]' could be streamlined). Overall, it's efficient and front-loaded, with every sentence adding necessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (13 parameters, no annotations, schema coverage 0%), the description does a good job of providing context. It explains all parameters thoroughly and notes an output schema exists ('Returns: str'), so it doesn't need to detail return values. However, it lacks behavioral context like auth or error handling, which slightly reduces completeness for a tool of this scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the full burden of explaining parameters. It comprehensively documents all 13 parameters with names, types, defaults, and semantic details (e.g., 'RFC 3339 timestamp' for date bounds, interactions like 'show_hidden must also be true'). This adds significant value beyond the bare schema, fully compensating for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 tasks in a specific task list.' It specifies the verb ('List') and resource ('tasks in a specific task list'), making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'get_task' or 'search_custom', which could also retrieve tasks, 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.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_task' (for single tasks) or 'search_custom' (for filtered searches), nor does it specify prerequisites or exclusions. This lack of context leaves the agent without clear usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 adds some context beyond the basic purpose: it specifies that modifications are partial (optional parameters), describes the return value (confirmation message with link), and includes details like format examples (RFC3339, JSON reminders) and constraints (max 5 reminders). However, it lacks critical behavioral info such as authentication requirements, error conditions, rate limits, or whether changes are reversible.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose statement followed by detailed parameter documentation in a consistent format. It's appropriately sized for a complex tool with many parameters, though some sentences could be more concise (e.g., the reminders explanation is lengthy). Every section adds value, but the structure is more documentation-heavy than conversational.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (13 parameters, mutation operation) and lack of annotations, the description does well: it explains the purpose, documents all parameters thoroughly, and describes the return value. However, it's incomplete for a mutation tool—missing authentication needs, error handling, and behavioral constraints like idempotency or side effects. The output schema exists, so return values are covered, but other gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides extensive parameter semantics beyond the input schema, which has 0% description coverage. For each of the 13 parameters, it adds meaning: clarifies required vs. optional, gives defaults (e.g., calendar_id default: 'primary'), explains formats (e.g., RFC3339 for times, JSON for reminders), provides examples, and describes behavior (e.g., add_google_meet: True adds, False removes, None leaves unchanged). This fully compensates for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 'Modifies an existing event,' specifying the verb (modifies) and resource (event). It distinguishes from sibling tools like 'create_event' (creation) and 'delete_event' (deletion), but doesn't explicitly contrast with similar tools like 'update_task' or 'modify_doc_text' beyond the event domain.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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., event must exist), compare to sibling tools like 'create_event' or 'get_events', or specify scenarios where it's appropriate (e.g., partial updates vs. full replacements). Usage is implied only by the tool name and purpose statement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 but doesn't describe rate limits, authentication requirements (beyond the user_google_email parameter), error handling, or performance characteristics. The Returns section describes output format, but behavioral traits like network dependencies or pagination are omitted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (Args, Returns) and uses bullet-like formatting for parameters. It's appropriately sized for a 12-parameter tool, though some sentences could be more front-loaded (e.g., the core purpose is stated first, but parameter details dominate).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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, no annotations, but has output schema), the description is fairly complete. It explains parameters thoroughly and includes output format, though it lacks behavioral context (e.g., error cases, rate limits). The output schema reduces the need for return value details, but more operational guidance would help.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must fully compensate. It provides detailed parameter documentation with examples (e.g., 'd5' for date_restrict, 'lang_en' for language), default values, and constraints (e.g., '1-10' for num). This adds substantial meaning beyond the bare schema, making parameters understandable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Performs a search') and resource ('using Google Custom Search JSON API'), distinguishing it from sibling tools like search_docs or search_drive_files. It precisely identifies the search engine being used, which is crucial for differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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_custom_siterestrict or other search tools in the sibling list. It lacks context about prerequisites (e.g., Google authentication setup) or typical use cases, leaving the agent with no usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 correctly identifies this as a creation operation and specifies the return format, but lacks details about authentication requirements, error conditions, rate limits, or whether the operation is idempotent. The description adds basic context but misses important behavioral traits for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, args, returns) and every sentence adds value. It's appropriately sized for a tool with 7 parameters and efficiently communicates essential information without redundancy or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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, the description does well by documenting all parameters and specifying the return format. However, it lacks information about authentication requirements, error handling, and how this tool relates to siblings. The presence of an output schema reduces the need to explain return values, but more behavioral context would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Given 0% schema description coverage, the description compensates fully by providing detailed parameter documentation. It clearly explains all 7 parameters, their purposes, data types, optionality, and even provides format examples (e.g., RFC 3339 for 'due'). This adds significant value beyond what the bare schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create a new task') and resource ('in a task list'), making the purpose immediately understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'create_task_list' or 'update_task', which would require a more specific 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.
Usage Guidelines2/5
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_task_list' (for creating task lists) or 'update_task' (for modifying existing tasks). It also doesn't mention prerequisites such as needing an existing task list ID or appropriate permissions, leaving usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. While it mentions the tool performs a 'move' operation (implying mutation), it doesn't disclose important behavioral aspects like required permissions, whether the move is reversible, error conditions, or rate limits. The description adds some context about what gets moved but lacks comprehensive behavioral disclosure for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose statement followed by organized 'Args' and 'Returns' sections. While slightly longer than minimal, every sentence earns its place by explaining parameter purposes. The front-loaded purpose statement is effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with 6 parameters and no annotations, the description does a good job explaining parameter semantics. The existence of an output schema means the description doesn't need to detail return values. However, it could better address behavioral aspects like permissions or error handling given it's a write operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 the purpose of each parameter in the 'Args' section. It clarifies that 'parent' is for making a task a subtask, 'previous' is for positioning, and 'destination_task_list' is for moving between lists. This adds significant meaning beyond the bare parameter names in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Move a task') and the possible destinations ('different position or parent within the same list, or to a different list'). It distinguishes this tool from sibling tools like 'create_task', 'delete_task', 'update_task', and 'list_tasks' by focusing specifically on repositioning tasks within or between lists.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage scenarios (moving within same list vs. between lists, changing parent/position) but doesn't explicitly state when to use this tool versus alternatives like 'update_task' for other modifications or 'create_task' for new tasks. No explicit exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 tool performs searches and returns formatted results, but doesn't cover important aspects like authentication requirements (implied by user_google_email but not explained), rate limits, error conditions, or what 'formatted' means. The description provides basic function but lacks behavioral depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, Args, Returns). Each sentence earns its place, though the Returns section could be slightly more informative. The front-loaded purpose statement is clear, and the parameter documentation is organized efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (6 parameters, no annotations, but has output schema), the description is reasonably complete. It covers all parameters thoroughly, states the purpose clearly, and mentions the return format. The output schema existence means the description doesn't need to detail return values. The main gap is lack of behavioral context like authentication or error handling.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 all 6 parameters in the Args section. It clarifies required vs optional parameters, provides defaults, ranges (1-10 for num), and enum values for safe. The only minor gap is not explaining the format/expectations for the sites parameter beyond 'List of sites/domains'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 ('Performs a search') and resource ('restricted to specific sites using Google Custom Search'). It distinguishes from sibling tools like 'search_custom' (unrestricted search) and other search tools by explicitly mentioning site restriction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through the tool name and description ('restricted to specific sites'), suggesting it should be used when limiting search to particular domains. However, it doesn't explicitly state when to choose this over alternatives like 'search_custom' or other search 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.
Behavior3/5
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 partially succeeds by describing the return value (confirmation message with event link) and some behavioral aspects like default values for 'calendar_id', 'add_google_meet', and 'use_default_reminders'. However, it lacks critical details such as error handling, rate limits, authentication requirements, or what happens with invalid inputs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (Args, Returns) and efficiently documents each parameter without redundancy. However, the 'Args' section is lengthy due to the high parameter count, and the opening line 'Creates a new event.' is somewhat redundant with the tool name, though it serves as a brief summary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (13 parameters, no annotations, but with output schema), the description is largely complete. It thoroughly documents parameters and return values, though it could improve by adding usage context (e.g., authentication needs, error cases). The output schema exists, so the description appropriately focuses on input semantics and high-level behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must fully compensate. It does so comprehensively by documenting all 13 parameters with clear semantics, data types, examples (e.g., RFC3339 format for times), constraints (e.g., max 5 reminders), and default values. This adds significant value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 ('Creates') and resource ('new event'), making it immediately understandable. It distinguishes from sibling tools like 'modify_event' and 'delete_event' by focusing on creation rather than modification or deletion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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), when to choose 'create_event' over 'modify_event', or any limitations (e.g., calendar permissions). 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.
Behavior2/5
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 the tool retrieves content but doesn't disclose behavioral traits like authentication requirements (implied by user_google_email but not explicit), rate limits, error conditions, or whether it's read-only (implied but not stated). The description adds minimal context beyond basic functionality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose in the first sentence. The Args and Returns sections are clear and necessary, with zero wasted words. Every sentence earns its place by providing essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 2 parameters with 0% schema coverage and an output schema (returns str), the description adequately covers the tool's purpose and parameters. However, as a read operation with no annotations, it could benefit from more behavioral context (e.g., auth needs, error handling). The output schema reduces the need to explain return values in the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 explains both parameters: message_id ('unique ID of the Gmail message to retrieve') and user_google_email ('user's Google email address. Required.'). This adds meaningful semantics beyond the schema's bare titles, though it doesn't detail format constraints (e.g., email validation).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Retrieves'), resource ('full content of a specific Gmail message'), and scope ('subject, sender, plain text body'). It distinguishes from sibling tools like 'get_gmail_messages_content_batch' (batch retrieval) and 'get_gmail_thread_content' (thread-level).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving a single message's content, but doesn't explicitly state when to use this vs. alternatives like batch retrieval tools or when not to use it (e.g., for metadata only). No prerequisites or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 clearly indicates this is a mutation tool ('modifies', 'update'), describes the operation type (insert/replace/format), and mentions the return format (confirmation message). However, it lacks critical behavioral details like required permissions, error conditions, or rate limits that would help the agent use it safely and effectively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose statement followed by organized parameter explanations. While efficient, the parameter section could be slightly more concise by grouping formatting parameters. Every sentence adds value, and the structure helps the agent quickly understand the tool's functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex mutation tool with 10 parameters, 0% schema coverage, and no annotations, the description does an excellent job explaining the tool's purpose and parameters. The presence of an output schema reduces the need to describe return values. The main gap is lack of behavioral context like permissions or error handling, but overall it's quite complete given the constraints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Given 0% schema description coverage, the description provides excellent parameter semantics beyond the bare schema. It explains the purpose of each parameter, clarifies optional vs. required behavior (e.g., 'if not provided with text, text is inserted'), and provides examples (font family names). This fully compensates for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 specific verbs ('modifies', 'insert/replace', 'apply formatting') and resource ('text in a Google Doc'). It distinguishes itself from sibling tools like 'find_and_replace_doc' by emphasizing single-operation text and formatting modifications, not just search-and-replace.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'batch_update_doc' or 'insert_doc_elements'. It mentions the operation scope but lacks explicit when-to-use or when-not-to-use instructions, leaving the agent to infer usage context from sibling tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the tool's write/update/clear capabilities and mentions a confirmation message return, but lacks details on permissions needed, error conditions, rate limits, or whether modifications are reversible. It adds basic behavioral context but misses important operational details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a purpose statement followed by Args and Returns sections. Every sentence earns its place by explaining functionality or parameters. It could be slightly more concise by integrating the Args explanations into the main description, but overall it's efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with 6 parameters, 0% schema coverage, no annotations, but with an output schema (Returns section), the description is moderately complete. It covers parameter semantics well and mentions the return confirmation, but lacks behavioral context like permissions, side effects, or error handling that would be important for a write operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 provides clear semantics for all 6 parameters: explains 'user_google_email' as the user's email, 'spreadsheet_id' as the spreadsheet ID, 'range_name' format examples, 'values' as a 2D array with format options, 'value_input_option' interpretations, and 'clear_values' purpose. This adds substantial meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('modifies') and resource ('values in a specific range of a Google Sheet'), with specific actions ('write, update, or clear values'). It distinguishes from siblings like 'read_sheet_values' (read-only) and 'create_spreadsheet' (creation tool).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for modifying sheet values but doesn't explicitly state when to use this tool versus alternatives like 'batch_update_doc' or 'modify_doc_text'. It mentions the 'clear_values' parameter for clearing ranges, providing some contextual guidance but no explicit when/when-not rules.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses the creation behavior and mentions shared drive support, but doesn't cover important aspects like required permissions, rate limits, error conditions, or whether the operation is idempotent. For a write operation 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear opening statement followed by organized Args and Returns sections. While efficient, the parameter explanations could be slightly more concise, and the opening sentence could be more front-loaded with the core purpose before diving into details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a 6-parameter file creation tool with no annotations, the description does well by explaining all parameters and mentioning shared drive support. However, it lacks behavioral context about permissions, errors, and limitations. The presence of an output schema reduces the need to explain return values, but more operational guidance would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
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 all 6 parameters in detail. It clarifies the purpose of user_google_email, distinguishes between content and fileUrl options, explains folder_id defaults and shared drive requirements, and specifies mime_type defaults. This adds substantial meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Creates a new file'), resource ('in Google Drive'), and scope ('supporting creation within shared drives'), distinguishing it from sibling tools like create_doc or create_spreadsheet that create specific file types. It precisely defines what the tool does beyond just restating the name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by mentioning shared drives and the content/fileUrl options, but doesn't explicitly state when to use this tool versus alternatives like create_doc for Google Docs or create_spreadsheet for Sheets. No explicit exclusions or prerequisites are provided, leaving some ambiguity about tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 describes the tool's scope and parameter interactions (e.g., how `drive_id` affects listing), but lacks details on permissions, rate limits, pagination beyond `page_size`, or what happens on errors. This is adequate but has clear gaps for a mutation-like tool (listing implies read-only, but not explicitly stated).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear opening sentence followed by parameter explanations and a returns section. It's appropriately sized for the tool's complexity, though some sentences could be more concise (e.g., the `corpora` explanation is slightly verbose). Overall, it's efficient with minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (6 parameters, no annotations, but has output schema), the description is mostly complete. It covers parameter semantics thoroughly and includes a returns section, but lacks behavioral details like error handling or pagination beyond `page_size`. The output schema exists, so return values needn't be explained in detail, but more context on the tool's operation would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
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 fully. It provides detailed semantics for all 6 parameters beyond their titles, explaining their purposes, defaults, interactions (e.g., `drive_id` with `folder_id` and `corpora`), and usage scenarios. This adds significant value over the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Lists files and folders, supporting shared drives.' It specifies the verb ('Lists') and resource ('files and folders'), and mentions shared drive support. However, it doesn't explicitly differentiate from sibling tools like 'list_docs_in_folder' or 'search_drive_files', which would be needed for a score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use specific parameters (e.g., 'If `drive_id` is specified...', 'If `drive_id` is not specified...'), which helps guide usage. However, it doesn't explicitly mention when to use this tool versus alternatives like 'list_docs_in_folder' or 'search_drive_files', nor does it provide exclusions or prerequisites, preventing a score of 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It clearly indicates this is a creation/mutation operation and specifies the return format. However, it doesn't mention authentication requirements, rate limits, error conditions, or whether drafts are saved automatically to Gmail. The examples help but don't fully compensate for missing behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (description, args, returns, examples). While comprehensive, some information like the full parameter list could be considered redundant given the high schema coverage. The examples are helpful but make the description longer than strictly necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 9-parameter mutation tool with no annotations but high schema coverage and an output schema, the description provides good coverage. It explains the tool's purpose, parameter relationships, and includes practical examples. However, it lacks information about authentication, error handling, and Gmail-specific constraints that would be valuable for a mutation operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 89% schema description coverage, the schema already documents most parameters well. The description adds valuable context by explaining the relationship between thread_id and reply drafts, and clarifying that 'to' can be empty for drafts. The examples provide practical usage patterns that enhance understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Creates a draft email') and resource ('in the user's Gmail account'), distinguishing it from sibling tools like send_gmail_message. It explicitly mentions support for both new drafts and reply drafts, providing comprehensive purpose information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context about when to use this tool (creating drafts vs. sending emails) and distinguishes between new drafts and reply drafts. However, it doesn't explicitly mention when NOT to use it or name specific alternatives among the sibling tools, though the distinction from send_gmail_message is implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 effectively describes the core functionality (adding/removing labels) and practical use cases (archiving/deleting via label changes), which is valuable. However, it lacks details on permissions required, error conditions (e.g., invalid label IDs), or rate limits, leaving gaps for a mutation 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized, with a clear purpose statement upfront, followed by usage examples and parameter details. Every sentence adds value, but the 'Args' and 'Returns' sections could be integrated more seamlessly into the narrative flow, slightly affecting readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, mutation operation) and no annotations, the description does a good job covering purpose, usage, and parameters. The presence of an output schema (indicated by 'Returns' in the description) reduces the need to detail return values. However, it could benefit from more behavioral context (e.g., error handling) to be fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50% (only 'add_label_ids' and 'remove_label_ids' have descriptions in the schema). The description compensates by listing all parameters with brief explanations in the 'Args' section, adding meaning beyond the schema for 'user_google_email' and 'message_id'. This improves understanding, though it doesn't fully elaborate on parameter formats or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Adds or removes labels from a Gmail message') and resource ('a Gmail message'), distinguishing it from sibling tools like 'manage_gmail_label' (which likely manages labels themselves) and 'batch_modify_gmail_message_labels' (which handles multiple messages). The purpose is precise and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool by explaining how to achieve specific outcomes (e.g., 'To archive an email, remove the INBOX label. To delete an email, add the TRASH label.'). However, it does not explicitly mention when NOT to use it or compare it to the sibling 'batch_modify_gmail_message_labels' for handling multiple messages, which would be helpful for differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses key behavioral traits: the atomic nature (all-or-nothing execution), batch capability, and operation types with examples. It mentions a return confirmation but doesn't detail error handling, permissions, or rate limits, leaving some gaps for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, args, example, returns) and front-loaded key information. It's appropriately sized but includes some redundancy (e.g., repeating 'operations' in the example). Every sentence adds value, though minor trimming is possible.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (batch mutations with nested operations), no annotations, and an output schema (returns str), the description is largely complete. It covers purpose, parameters, and behavioral context but could enhance completeness by addressing prerequisites (e.g., authentication) or error scenarios, though the output schema mitigates return value explanation needs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
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 fully. It adds substantial meaning: it explains user_google_email as 'User's Google email address,' document_id as 'ID of the document to update,' and operations with detailed structure, types, and examples, effectively documenting all three parameters beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Executes multiple document operations in a single atomic batch update.' It specifies the verb ('executes'), resource ('document operations'), and key characteristic ('atomic batch'), distinguishing it from single-operation siblings like modify_doc_text or insert_doc_elements.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by mentioning 'multiple document operations in a single atomic batch,' suggesting efficiency for bulk edits. However, it lacks explicit guidance on when to use this tool versus alternatives like modify_doc_text or when not to use it (e.g., for single operations). No sibling tools are directly compared.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 describes the tool's dual retrieval modes, parameter interactions, and default behaviors (e.g., 'calendar_id' defaults to 'primary', 'time_min' defaults to current time). However, it doesn't mention authentication requirements, rate limits, error conditions, or whether this is a read-only operation (though 'retrieves' implies reading).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose statement upfront, followed by detailed parameter explanations in a formatted 'Args' section and a 'Returns' section. While comprehensive, some sentences could be more concise (e.g., the parameter explanations are thorough but slightly verbose). Every section adds value, with no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 8 parameters, 0% schema description coverage, no annotations, but with an output schema, the description provides excellent parameter semantics and clear purpose. The output schema handles return value documentation, so the description appropriately focuses on usage and parameters. It could improve by adding more behavioral context (e.g., authentication, errors) given the lack of annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Given 0% schema description coverage, the description fully compensates by providing detailed semantic explanations for all 8 parameters. It clarifies required vs. optional parameters, default values, format requirements (e.g., RFC3339), parameter interactions (e.g., 'event_id' overrides time filtering), and practical usage notes (e.g., 'Use 'primary' for the user's primary calendar', 'Calendar IDs can be obtained using `list_calendars`').
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Retrieves events') and resource ('from a specified Google Calendar'), distinguishing it from sibling tools like 'create_event', 'modify_event', and 'delete_event' which perform different operations on calendar events. It also specifies the dual retrieval modes (single event by ID or multiple events within time range).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for usage by explaining the two primary modes (single event retrieval vs. time-range retrieval) and how parameters interact (e.g., 'event_id' overrides time filtering parameters). However, it doesn't explicitly state when to use this tool versus alternatives like 'list_calendars' (a sibling tool) or mention any prerequisites beyond the required parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 describes the search scope and result format, but doesn't mention important behavioral aspects like authentication requirements, rate limits, pagination behavior beyond page_size, or whether this is a read-only operation. The description adds some value but 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with clear sections (description, Args, Returns). The description sentence is efficient, and parameter explanations are necessary given the 0% schema coverage. Could be slightly more concise in the corpora explanation, but overall earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (6 parameters, 0% schema coverage, no annotations) and the presence of an output schema, the description does well. It thoroughly documents parameters and describes the return format. However, for a search tool with no annotations, it could better address behavioral aspects like authentication, rate limits, and error conditions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates excellently by providing detailed parameter explanations. Each parameter gets clear semantics: user_google_email is 'required', query 'supports Google Drive search operators', page_size has a default, drive_id behavior is explained, include_items_from_all_drives has default and condition, and corpora gets detailed usage guidance with efficiency recommendations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 specific verb ('searches') and resource ('files and folders within a user's Google Drive, including shared drives'). It distinguishes itself from sibling tools like 'list_drive_items' by emphasizing search functionality rather than simple listing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context about when to use this tool (searching within Google Drive) and mentions scope (including shared drives). However, it doesn't explicitly state when NOT to use it or name specific alternatives like 'list_drive_items' for non-search scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 discloses that the tool sends emails (a write operation) and returns a confirmation message, which is basic behavioral context. However, it lacks details on permissions required (e.g., Gmail API scopes), rate limits, error handling, or whether it modifies existing data (e.g., thread updates), leaving gaps for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized: it starts with a clear purpose statement, followed by organized sections for Args, Returns, and Examples. Every sentence adds value, such as explaining parameter roles and demonstrating use cases, with no redundant or verbose content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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, mutation operation) and no annotations, the description does a good job covering purpose, parameters, and examples. An output schema exists (implied by 'Returns'), so explaining return values isn't needed. However, it lacks details on behavioral aspects like authentication or error handling, which are important for a send-email tool, preventing a perfect score.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is high (89%), so the baseline is 3. The description adds value by grouping parameters in the 'Args' section with brief explanations and providing examples that illustrate usage patterns (e.g., how 'thread_id' enables replies). This enhances understanding beyond the schema, though it doesn't fully compensate for the 11% coverage gap (e.g., 'user_google_email' lacks description in schema).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Sends an email using the user's Gmail account. Supports both new emails and replies.' It specifies the verb ('sends'), resource ('email'), and distinguishes its dual functionality (new emails and replies) from sibling tools like 'draft_gmail_message' (which only drafts) and 'send_message' (which is generic).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for usage: 'Supports both new emails and replies' and includes examples showing when to use it for new emails versus replies. However, it does not explicitly state when not to use it (e.g., vs. 'draft_gmail_message' for drafting without sending) or mention alternatives, which prevents a perfect score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does well by detailing behavioral traits: it specifies how different file types are processed (exported, parsed, or downloaded), notes encoding attempts, and mentions a metadata header in returns. It doesn't cover aspects like rate limits or auth needs beyond the user email parameter, but provides substantial 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the core purpose, followed by bullet points for file type handling and a clear 'Args'/'Returns' section. Every sentence adds value without redundancy, making it efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (handling multiple file types) and no annotations, the description is complete: it explains the tool's purpose, behavioral details, parameters, and return value. With an output schema present, it doesn't need to elaborate on return structure, and it adequately covers the context needed for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 meaning by explaining that 'user_google_email' is for the user's Google email and 'file_id' is the Drive file ID, clarifying their roles beyond the schema's basic titles. However, it doesn't specify format details or constraints for these parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('retrieves') and resource ('content of a specific Google Drive file by ID'), specifying it works with files in shared drives. It distinguishes itself from siblings like 'get_doc_content' by focusing on generic Drive file content retrieval across formats, not just Docs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by detailing supported file types and processing methods, suggesting it's for extracting text from various Drive files. However, it doesn't explicitly state when to use this tool versus alternatives like 'get_doc_content' or 'list_drive_items', 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.
Behavior4/5
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 effectively describes key behaviors: it's a search operation (implies read-only), returns structured results with IDs and web links, and mentions the default page_size. However, it doesn't cover potential limitations like rate limits, authentication requirements beyond the email parameter, or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly structured and front-loaded: the first sentence states the core purpose, subsequent sentences add important details about returns and verification, and the parameter/return sections are clearly organized. Every sentence earns its place with no wasted words, making it easy for an AI agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, search functionality) and the presence of an output schema (though not shown here, the Returns section describes it), the description is complete enough. It covers purpose, parameters, returns, and verification aspects. With no annotations, it provides adequate behavioral context for a search tool, and the output description reduces the need for further return value explanation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
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 providing detailed parameter documentation. It explains all three parameters: 'query' supports Gmail search operators, 'user_google_email' is required, and 'page_size' has a default of 10. This adds significant value beyond the bare schema which only provides titles and types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 specific verb ('searches') and resource ('messages in a user's Gmail account'), and distinguishes it from siblings like 'search_messages' by specifying Gmail context and mentioning Message IDs, Thread IDs, and Gmail web interface links. It provides a complete picture of what the tool does beyond just the name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for searching Gmail messages with query-based filtering, but doesn't explicitly state when to use this tool versus alternatives like 'search_messages' or 'get_gmail_message_content'. It provides context about returning IDs and web links for verification, but lacks explicit guidance on when this tool is preferred over other search or retrieval tools in the sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses important behavioral traits: the batch size limit (25 threads), automatic chunking behavior, and the formatted return format. It doesn't mention authentication requirements, rate limits, or error handling, but provides substantial 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly structured: a clear purpose statement, a practical constraint, then organized parameter and return sections. Every sentence earns its place with zero wasted words. The information is front-loaded with the most important details first.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 2-parameter tool with no annotations but with an output schema, the description provides excellent coverage of purpose, constraints, and parameter semantics. The output schema handles return value details, so the description appropriately focuses on operational context. It could potentially mention authentication scope but is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
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: 'thread_ids' as 'A list of Gmail thread IDs to retrieve' with automatic batching behavior, and 'user_google_email' as 'The user's Google email address' marked as required. This adds crucial meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('retrieves the content'), resource ('multiple Gmail threads'), and scope ('in a single batch request'). It distinguishes from sibling tools like 'get_gmail_thread_content' (singular) and 'get_gmail_messages_content_batch' (messages vs threads).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context about when to use this tool ('multiple Gmail threads in a single batch request') and includes a practical constraint ('Supports up to 25 threads per batch to prevent SSL connection exhaustion'). However, it doesn't explicitly mention when NOT to use it or name specific alternatives like the singular thread content tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 effectively describes key behavioral traits: it's a read operation (implied by 'retrieves'), has a batch limit (25 messages), mentions a technical rationale (SSL exhaustion), and specifies the return format (formatted list with separators). It doesn't cover error handling or authentication details, but provides substantial context beyond basic functionality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly structured and front-loaded: the first sentence states the core purpose, the second adds important constraints, followed by well-organized Args and Returns sections. Every sentence earns its place with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (batch operation with constraints), no annotations, and the presence of an output schema (implied by Returns section), the description is complete. It covers purpose, constraints, all parameters with semantics, and return format, providing everything needed for correct tool selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
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 all three parameters: message_ids (list of IDs with max 25), user_google_email (required user email), and format (enum values with clear semantics: 'full' includes body, 'metadata' only headers). This adds crucial meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 specific verbs ('retrieves the content of multiple Gmail messages') and distinguishes it from siblings like 'get_gmail_message_content' (singular) and 'get_gmail_threads_content_batch' (threads vs messages). It specifies the batch nature and resource scope (Gmail messages).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool (batch retrieval of up to 25 messages) and mentions a technical constraint (preventing SSL connection exhaustion). However, it doesn't explicitly state when NOT to use it or name specific alternatives like the singular version or thread-based batch tool, which would elevate it to a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 effectively explains what the tool does (inspects document structure), why it's important (for safe insertion), and what the output contains. However, it doesn't mention potential limitations, error conditions, or performance characteristics that would be helpful for an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, usage, critical notes, output details, workflow, args, returns) but could be more concise. Some sections like the workflow could be simplified, and the description uses 14 sentences where fewer might suffice while maintaining clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (structural analysis with safety implications) and the presence of an output schema, the description is remarkably complete. It explains the purpose, usage scenarios, critical workflow integration, output interpretation, and parameter semantics, providing everything an agent needs to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage for 3 parameters, the description compensates well by explaining the 'detailed' parameter's purpose ('Whether to return detailed structure information') in the Args section. However, it doesn't explain the semantics of 'user_google_email' or 'document_id' beyond what the schema titles provide.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as finding safe insertion points and understanding document structure, with specific verbs like 'finding', 'understanding', 'locating', and 'getting'. It distinguishes itself from sibling tools by focusing on document structure inspection rather than creation, modification, or content retrieval operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance with a 'USE THIS FOR' section listing specific scenarios and a 'CRITICAL FOR TABLE OPERATIONS' section mandating when to call it ('ALWAYS call this BEFORE creating tables'). It also includes a detailed workflow with numbered steps, making it clear when and how to use this tool versus alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does so well by detailing what the tool returns (e.g., 'Exact table dimensions,' 'Current content in each cell'), how to interpret the output (e.g., 'dimensions: "2x3"'), and its read-only nature implied by debugging use. It lacks explicit rate limits or auth needs, but covers core behavior thoroughly.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (e.g., 'USE THIS IMMEDIATELY WHEN,' 'HOW TO READ THE OUTPUT,' 'WORKFLOW INTEGRATION') and uses bullet points for readability. It is slightly verbose but every sentence adds value, such as explaining output interpretation and integration steps, making it efficient for an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (debugging table structure), no annotations, 0% schema coverage, and an output schema provided, the description is complete. It explains purpose, usage, parameters, output format (e.g., 'Detailed JSON structure'), and integration, leaving no gaps for the agent to understand and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates fully by explaining all three parameters in the 'Args' section: 'user_google_email: User's Google email address,' 'document_id: ID of the document to inspect,' and 'table_index: Which table to debug (0 = first table, 1 = second table, etc.).' This adds crucial meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool's purpose as an 'ESSENTIAL DEBUGGING TOOL' for table structure issues, specifying it shows table dimensions, cell positions, content, and insertion indices. It clearly distinguishes from sibling tools like 'create_table_with_data' or 'populate_existing_table' by focusing on inspection rather than creation or modification.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage scenarios with bullet points (e.g., 'Table population put data in wrong cells,' 'Need to understand existing table structure') and a detailed workflow integration section (e.g., 'After creating table → Use this to verify structure'). It clearly differentiates when to use this tool versus alternatives like 'populate_existing_table' for planning.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 effectively explains that this tool triggers a manual authentication flow, contrasting it with the automatic authentication handled by other tools. It mentions failure scenarios and retry logic, though it doesn't detail what happens during the flow (e.g., user prompts, token storage) or error handling specifics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose, followed by important usage notes. Every sentence adds value: the first states the purpose, the second warns against typical use, the third lists specific use cases, and the fourth reinforces the alternative. There is no wasted text, and the information is efficiently organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (authentication flow with 2 parameters) and the presence of an output schema (which handles return values), the description is complete. It covers purpose, usage guidelines, and behavioral context adequately, and the output schema likely details authentication results, so no additional return value explanation is needed in the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 the lack of parameter documentation. While it doesn't explicitly mention the two parameters (service_name, user_google_email), it implies their purpose by discussing authentication for Google services and user credentials. The context about 'different credentials' and 'Google Workspace tools' helps infer parameter roles, though direct parameter explanation would improve this.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool's purpose: 'Manually initiate Google OAuth authentication flow.' This is a specific verb ('initiate') with a clear resource ('Google OAuth authentication flow'), and it distinguishes itself from all sibling tools, which are Google Workspace operations rather than authentication utilities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when NOT to use this tool ('typically NOT be called directly') and lists three specific scenarios for its use (re-authenticate with different credentials, proactive authentication, retry after failure). It also mentions the alternative approach of letting other tools handle authentication automatically, making the usage context very clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and delivers comprehensive behavioral disclosure. It explains the critical index requirements, data format constraints, validation needs, and the reliable operation nature. It also mentions post-creation verification with debug_table_structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized for a complex tool but could be more front-loaded. The critical information is emphasized with headers, but the workflow steps and examples are lengthy. Every sentence earns its place by providing essential guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (5 parameters, 0% schema coverage, no annotations) and presence of output schema, the description is remarkably complete. It covers purpose, prerequisites, workflow, parameter semantics, constraints, examples, and post-operation verification, leaving no significant gaps for agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
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 all 5 parameters. It clarifies table_data format with detailed examples, explains index requirements and source, specifies bold_headers default behavior, and contextualizes document_id and user_google_email within the workflow.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific verb 'creates' and resource 'table', and distinguishes it from siblings by specifying it 'populates it with data in one reliable operation'. This differentiates it from other creation tools like create_doc or create_spreadsheet that don't mention data population.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit, mandatory workflow steps including when to use (ALWAYS call inspect_doc_structure first) and alternatives (use debug_table_structure after creation to verify results). It gives clear prerequisites and sequencing requirements.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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