Hardened Google Workspace MCP

by c0webster

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v1.7.1
Disambiguation4/5
Most tools have distinct purposes targeting specific Google Workspace services (Docs, Sheets, Gmail, Drive, Calendar, Forms, Slides), with clear resource-action pairs like create_doc vs. modify_doc_text. However, some overlap exists between get_doc_content and get_drive_file_content for document retrieval, and between various comment tools across services, which could cause minor confusion.
Naming Consistency5/5
Tool names follow a highly consistent verb_noun pattern throughout, using snake_case uniformly. Examples include create_doc, modify_event, list_calendars, and get_spreadsheet_info. The naming convention is predictable and readable across all 73 tools.
Tool Count2/5
With 73 tools, the set is excessively large for a single server, making it overwhelming and difficult for agents to navigate. While Google Workspace is broad, this count feels heavy and could lead to tool selection paralysis, as many tools are highly specific (e.g., separate comment tools for Docs, Sheets, and Presentations).
Completeness5/5
The tool surface provides comprehensive coverage across Google Workspace services, including full CRUD operations for Docs, Sheets, Slides, Calendar events, Drive files, Gmail, and Forms. It also includes advanced features like conditional formatting, batch operations, and debugging tools, leaving no obvious gaps for the domain.
Average 3.4/5 across 73 of 73 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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- No critical vulnerability alerts
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This repository is licensed under MIT License.
This repository includes a README.md file.
Tools from this server were used 4 times in the last 30 days.
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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 does not mention whether this operation is destructive (e.g., marking a comment as resolved vs. deleting it), what permissions are required, or any side effects like notifications. This leaves critical behavioral traits undocumented.
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 that states the tool's purpose without unnecessary words. It is front-loaded and efficiently communicates the core action, making it easy to parse quickly.
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 complexity of a mutation tool (resolving comments likely changes state) with no annotations, 0% schema description coverage, and an output schema (which helps but isn't described), the description is incomplete. It lacks details on behavior, parameters, and 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.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, and the description provides no information about the parameters. It does not explain what 'user_google_email', 'document_id', or 'comment_id' represent, their formats, or how to obtain them, failing to compensate for the schema's lack of 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 ('Resolve') and target ('a comment in a Google Document'), providing a specific verb+resource combination. However, it does not explicitly differentiate from sibling tools like 'resolve_presentation_comment' or 'resolve_spreadsheet_comment', which perform similar actions on different Google Workspace resources, leaving some ambiguity in distinguishing between them.
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 offers no guidance on when to use this tool versus alternatives, such as 'reply_to_document_comment' or other comment-related tools. It lacks context about prerequisites (e.g., needing an unresolved comment) or exclusions, providing minimal usage direction 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 but offers minimal behavioral insight. It mentions that the tool retrieves form details, implying a read operation, but doesn't disclose authentication needs, rate limits, error conditions, or what happens if the form doesn't exist. The Returns section describes output content, but this is basic and lacks 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 appropriately sized and structured with clear sections (Args, Returns). It's front-loaded with the core purpose, and each sentence adds value without redundancy. However, the initial 'Get a form.' is overly terse and 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 the tool has an output schema (true) and no annotations, the description is moderately complete. It covers parameters and return values, but lacks context on authentication, error handling, or sibling tool differentiation. For a simple retrieval tool, this is adequate but not thorough.
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 adds parameter semantics in the Args section, explaining that 'user_google_email' is the user's Google email address (required) and 'form_id' is the ID of the form to retrieve. This compensates somewhat for the lack of schema 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.
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 quite basic and doesn't differentiate from sibling tools like 'get_form_response' or 'get_presentation'. It specifies what is retrieved but lacks specificity about scope or constraints beyond the parameters.
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 'get_form_response' or 'list_form_responses'. The description doesn't mention prerequisites, context, or exclusions, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 offers minimal behavioral insight. It states the action (listing) and return type (formatted list), but doesn't disclose permissions needed, rate limits, pagination behavior (despite a 'page_size' parameter), or whether it's read-only/destructive. The mention of 'formatted list' adds some context, but key operational details are missing.
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 in the first sentence. The second sentence about return values is somewhat redundant given the output schema, 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 moderate complexity (3 parameters, no annotations, but with output schema), the description is incomplete. It covers the basic action and return format, but lacks parameter explanations, usage guidelines, and behavioral details. The output schema mitigates some gaps, but the description doesn't provide enough context 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 description must compensate but fails to do so. It doesn't explain any of the three parameters (user_google_email, folder_id, page_size), their purposes, formats, or constraints. The baseline would be lower than 3 due to poor coverage, and the description adds no parameter information beyond what's inferred from the tool name.
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 ('Lists') and resource ('Google Docs within a specific Drive folder'), making the purpose unambiguous. It distinguishes from siblings like 'list_drive_items' by specifying Google Docs only, though it doesn't explicitly contrast with 'search_docs' or other listing 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 like 'list_drive_items' or 'search_docs'. The description mentions the scope (Google Docs in a folder) but doesn't specify prerequisites, exclusions, or comparative use cases with 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Reply to') but doesn't mention required permissions, whether this is a write operation, potential side effects, rate limits, or what the output contains. 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, efficient sentence with zero waste, front-loading the core purpose. It's appropriately sized for the tool's complexity, 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 4 required parameters), no annotations, and 0% schema coverage, the description is incomplete. While an output schema exists, the description doesn't address behavioral aspects like permissions or side effects, leaving significant gaps for agent understanding.
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 by explaining parameters. It adds no meaning beyond what the schema provides—no clarification on what 'user_google_email', 'document_id', 'comment_id', or 'reply_content' represent, their formats, or examples. This fails to 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 action ('Reply to') and target resource ('a specific comment in a Google Document'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from its siblings like 'reply_to_presentation_comment' or 'reply_to_spreadsheet_comment' beyond the document type, missing explicit 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?
No guidance is provided on when to use this tool versus alternatives. The description lacks context about prerequisites (e.g., needing an existing comment), exclusions, or comparisons to sibling tools like 'create_document_comment' or 'resolve_document_comment', 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 provided, the description carries the full burden of behavioral disclosure. It states the action but does not cover critical aspects like required permissions, whether replies are editable or permanent, rate limits, or error handling. 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, direct sentence with no wasted words, making it highly concise and front-loaded. It efficiently communicates the core action 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 the complexity of a mutation tool with no annotations, 0% schema coverage, and four required parameters, the description is insufficient. It lacks details on behavior, parameters, and usage context, though the presence of an output schema mitigates the need to explain return values.
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%, and the description does not explain any of the four parameters (e.g., what 'user_google_email' represents, how to obtain 'presentation_id' or 'comment_id', or constraints on 'reply_content'). This fails to compensate for the lack of schema documentation, leaving parameters ambiguous.
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 resource ('a specific comment in a Google Presentation'), making the purpose immediately understandable. However, it does not explicitly differentiate from sibling tools like 'reply_to_document_comment' or 'reply_to_spreadsheet_comment', which have similar structures but target different Google Workspace applications.
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, such as 'reply_to_document_comment' or 'reply_to_spreadsheet_comment', nor does it mention prerequisites like authentication or comment visibility. It lacks context for distinguishing between similar 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'resolves' a comment, implying a mutation operation, but does not clarify what 'resolve' entails (e.g., marking as resolved vs. deleting), whether it requires specific permissions, or what the output looks like. This leaves significant gaps in understanding the tool's behavior and effects.
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 is front-loaded with the core action and resource, making it easy to parse quickly. Every word contributes directly to stating the tool's purpose.
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 incomplete. While an output schema exists (which reduces the need to explain return values), the description does not address key contextual aspects like behavioral implications, parameter meanings, or usage guidelines, making it insufficient for informed tool selection.
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 input schema has 0% description coverage, meaning all three parameters are undocumented. The description does not add any meaning beyond the schema—it does not explain what 'user_google_email', 'spreadsheet_id', or 'comment_id' represent or how to obtain them. With low schema coverage, the description fails to compensate, leaving parameters semantically 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 action ('Resolve') and target resource ('a comment in a Google Spreadsheet'), providing a specific verb+resource combination. However, it does not distinguish this tool from sibling tools like 'resolve_document_comment' or 'resolve_presentation_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?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., needing an unresolved comment), exclusions, or comparisons to sibling tools like 'reply_to_spreadsheet_comment', leaving the agent to infer usage context solely from the tool name and 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 mentions the return format ('A formatted list') and the API used ('Drive API'), but lacks critical details: it doesn't specify whether this is a read-only operation, what permissions are required, how errors are handled, or if there are rate limits. For a search tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately concise with two sentences: one stating the purpose and method, and another describing the return value. It's front-loaded with the core functionality. However, the second sentence could be more efficiently integrated, and there's minor redundancy in specifying 'Google Docs' twice.
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 (search with 3 parameters), no annotations, and an output schema exists (implied by 'Returns: str'), the description is minimally adequate. It covers the basic action and return type but misses important context: parameter meanings, behavioral constraints, and differentiation from siblings. The output schema reduces the need to detail return values, but other gaps remain significant.
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 doesn't explain any of the three parameters (user_google_email, query, page_size) beyond what the schema's property names imply. The description mentions 'search query' generally but doesn't clarify the query syntax, the purpose of user_google_email, or how page_size affects results. This fails to add meaningful 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: 'Searches for Google Docs by name using Drive API (mimeType filter).' It specifies the verb ('Searches'), resource ('Google Docs'), and method ('using Drive API'), distinguishing it from general file search tools like 'search_drive_files' in the sibling list. However, it doesn't explicitly differentiate from other search tools beyond mentioning the mimeType filter.
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 when this tool is preferred over 'search_drive_files' or 'list_docs_in_folder' from the sibling list, nor does it specify prerequisites or exclusions. The only contextual hint is the mimeType filter, but this isn't framed as usage guidance.
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 'batch updates' but doesn't clarify whether this is a destructive operation, what permissions are required, whether changes are reversible, or if there are rate limits. The description lacks critical 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear opening statement followed by parameter and return value sections. Each sentence serves a purpose, though the parameter explanations could be more informative given the 0% schema coverage. No wasted words, but could benefit from more substantive content.
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 and no annotations, the description is minimally adequate. The presence of an output schema reduces the need to document return values, but critical behavioral aspects (permissions, destructiveness, error handling) are missing. The 0% schema description coverage means parameters are poorly documented, leaving significant 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 documentation. The description adds basic semantic context for each parameter (e.g., 'user's Google email address', 'ID of the presentation', 'List of update requests'), but doesn't explain the structure of update requests, valid formats, or examples. This provides minimal value beyond the bare parameter names.
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 ('Apply batch updates') and resource ('to a Google Slides presentation'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'update_doc' or 'modify_doc_text', which could cause confusion about when to use this specific presentation-focused tool versus other document editing 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 about when to use this tool versus alternatives. With many sibling tools for document/presentation editing (e.g., 'update_doc', 'modify_doc_text', 'create_presentation'), the description offers no context about prerequisites, when batch updates are appropriate, or what distinguishes this from single-update 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 mentions the tool 'searches' and 'checks', implying a read-only operation, but doesn't clarify permissions needed, rate limits, error handling, or what 'public link sharing enabled' entails (e.g., link visibility settings). The return value description is minimal, lacking details on format or potential outcomes.
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 concise at three sentences, with no redundant information. However, the 'Args' and 'Returns' sections could be integrated more fluidly into the main description for better flow.
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 basic purpose and parameters but lacks behavioral context, usage guidelines, and detailed return semantics. The output schema exists, so the description doesn't need to fully explain returns, but it should provide more operational guidance.
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 details. The description includes an 'Args' section that lists and briefly describes the two parameters ('user_google_email' and 'file_name'), adding basic semantics beyond the schema. However, it doesn't explain format expectations (e.g., email validation, file name matching) or constraints, leaving gaps in understanding.
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 a file by name and checks if it has public link sharing enabled.' This specifies the verb ('searches' and 'checks'), resource ('file'), and scope ('public link sharing'). However, it doesn't explicitly differentiate from sibling tools like 'get_drive_file_permissions' or 'get_drive_shareable_link', which might have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 'search_drive_files', 'get_drive_file_permissions', and 'get_drive_shareable_link', there's no indication of prerequisites, constraints, or comparative use cases. The description only states what it does, not when it's appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It states the tool creates a document and returns a confirmation message, but doesn't disclose important behavioral traits: required permissions (e.g., Google Drive access), whether it overwrites existing documents with same title, rate limits, or error conditions. The return format is mentioned but lacks detail on what happens on failure.
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 two sentences: one stating the core functionality and one describing the return. It's front-loaded with the main purpose. However, the second sentence about returns could be integrated more smoothly, and there's minor redundancy ('Creates' and 'new').
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, but with an output schema present, the description is moderately complete. It covers the basic action and return, but lacks context on permissions, error handling, or sibling differentiation. The output schema reduces the need to detail return values, but behavioral gaps remain significant for a creation 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 description must compensate. It mentions 'optionally inserts initial content' which clarifies the purpose of the content parameter, but doesn't explain user_google_email (e.g., whether this is the owner or just a user email) or title (format constraints, uniqueness). It adds some value but doesn't fully 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 tool creates a new Google Doc with optional initial content insertion. It specifies the verb ('Creates') and resource ('Google Doc'), distinguishing it from siblings like create_spreadsheet or create_presentation. However, it doesn't explicitly differentiate from create_drive_file which might also create documents, 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 like create_drive_file or batch_update_doc. It mentions optional content insertion but doesn't clarify scenarios where this is preferable over creating an empty doc and modifying it later. No exclusions or prerequisites are 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 the full burden of behavioral disclosure. It states the tool creates a comment but fails to mention critical details like required permissions, whether it's a mutating operation, rate limits, or what the output contains. 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, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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) and the presence of an output schema, the description is minimally adequate. However, it lacks details on parameter usage, behavioral context, and sibling differentiation, which are needed for full completeness despite the output schema covering return values.
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 parameters are undocumented in the schema. The description adds no information about the three required parameters (user_google_email, document_id, comment_content), such as their formats, examples, or constraints. It fails to compensate for the schema's lack of 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 a new comment') and resource ('on a Google Document'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'create_presentation_comment' or 'create_spreadsheet_comment' beyond specifying the document type, missing explicit 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?
No guidance is provided on when to use this tool versus alternatives like 'reply_to_document_comment' or 'resolve_document_comment'. The description lacks context about prerequisites, such as needing document access or authentication, 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 provided, the description carries the full burden of behavioral disclosure. It states the tool creates a comment but offers no details on permissions required (e.g., editor role), whether the comment is public or private, how it appears in the presentation, or what happens on failure. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding its behavior and constraints.
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 directly states the tool's action and target. It's front-loaded with the core purpose and wastes no words, making it easy to parse quickly. Every part of the sentence contributes essential information without 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 (a mutation with 3 parameters) and the presence of an output schema (which reduces the need to describe return values), the description is partially adequate. However, with no annotations and 0% schema coverage, it fails to address key aspects like parameter semantics, behavioral traits, and usage context, leaving the agent with insufficient information to use the tool effectively beyond its basic intent.
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 by explaining parameters, but it adds no meaning beyond what the schema provides. The three required parameters ('user_google_email', 'presentation_id', 'comment_content') are undocumented in both the schema and description, leaving their purposes, formats, and constraints unclear. The description doesn't even hint at what these parameters represent.
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 resource ('on a Google Presentation'), making the purpose immediately understandable. It distinguishes this tool from siblings like 'create_document_comment' and 'create_spreadsheet_comment' by specifying the presentation context, though it doesn't explicitly differentiate from 'reply_to_presentation_comment' or 'resolve_presentation_comment' in terms of comment type or state.
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 access to the presentation), compare it to sibling tools like 'reply_to_presentation_comment' or 'resolve_presentation_comment', or indicate scenarios where it's appropriate (e.g., initial feedback vs. threaded replies). Usage is implied only by the tool name and basic action.
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 but doesn't mention permission requirements, whether comments are editable/deletable, rate limits, or what the output contains. 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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized for a basic creation operation 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?
The description adequately covers the basic purpose of this tool, and the existence of an output schema means return values don't need explanation. However, for a mutation tool with 3 undocumented parameters and no annotations, the description should provide more context about permissions, behavior, and parameter usage 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 3 parameters, the description provides no semantic information about what 'user_google_email', 'spreadsheet_id', or 'comment_content' represent or how they should be formatted. The description doesn't compensate for the complete lack of parameter documentation in the 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 action ('Create a new comment') and target resource ('on a Google Spreadsheet'), providing specific verb+resource information. However, it doesn't differentiate from sibling tools like 'create_document_comment' or 'create_presentation_comment', which 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 on when to use this tool versus alternatives like 'reply_to_spreadsheet_comment' or 'read_spreadsheet_comments'. There's no mention of prerequisites, appropriate contexts, 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. While it states this is a deletion operation (implying a destructive mutation), it doesn't mention whether deletions are permanent, reversible, or have side effects. The confirmation message in the Returns section adds some value but doesn't fully describe 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 well-structured with clear sections (purpose, Args, Returns) and uses minimal wording. Every sentence serves a purpose, though the Args section could be slightly more concise by combining some details.
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 3 parameters and no annotations, the description is moderately complete. It covers parameters and return values, but lacks important context about authentication, error conditions, and behavioral implications. The existence of an output schema helps but doesn't fully compensate for these 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?
With 0% schema description coverage, the description compensates by documenting all three parameters in the Args section, including their types, required status, and default value for calendar_id. However, it doesn't explain what format event_id should be in or provide examples, leaving some semantic 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 with a specific verb ('Deletes') and resource ('an existing event'), making it immediately understandable. However, it doesn't differentiate this tool from its sibling 'modify_event' or other event-related tools, 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 like 'modify_event' or 'get_events'. It also doesn't mention prerequisites such as authentication requirements or permission levels needed to delete events.
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 metadata and permissions, implying a read-only operation, but doesn't specify authentication requirements, rate limits, error conditions, or what happens if the user lacks access. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior and constraints.
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 separate sections for Args and Returns. It's front-loaded with the main functionality and avoids unnecessary details. However, the 'Returns' section could be more concise by integrating with the purpose statement, and some sentences are slightly verbose.
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 but lacks behavioral details and usage guidelines. The output schema exists, so the description doesn't need to fully explain return values, but it still misses key 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.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes an 'Args' section that lists and briefly describes the two parameters, adding meaning beyond the input schema (which has 0% description coverage). However, it doesn't explain parameter formats (e.g., expected email pattern or file ID structure) or provide examples. With two parameters and low schema coverage, this offers basic but incomplete 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: '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'), which is clear and specific. However, it doesn't explicitly differentiate from sibling tools like 'check_drive_file_public_access' or 'get_drive_shareable_link', 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. It doesn't mention any prerequisites, exclusions, or comparisons to sibling tools such as 'check_drive_file_public_access' or 'get_drive_shareable_link'. The usage is implied by the purpose statement alone, with no explicit context for 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 tool 'gets' a shareable link, implying a read-only operation, but doesn't clarify if this requires specific permissions (e.g., viewer access), whether it modifies anything (e.g., changes sharing settings), or what happens on errors (e.g., if the file doesn't exist). For a tool with zero annotation coverage, this lack of behavioral details 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 appropriately sized and front-loaded: the first sentence states the purpose clearly, followed by structured sections for Args and Returns. There's no wasted text, and each section earns its place by organizing information logically. However, the Returns section could be more precise (e.g., specifying it returns a string vs. multiple links).
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 but lacks behavioral context (e.g., permissions, errors) and usage guidelines. The output schema exists, so the description doesn't need to detail return values, but the Returns section is somewhat vague ('The shareable links and current sharing status' might imply multiple outputs, while the schema suggests a single string).
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 details. The description adds basic semantics by listing parameters with brief explanations: 'user_google_email (str): The user's Google email address. Required.' and 'file_id (str): The ID of the file or folder to get the shareable link for. Required.' This clarifies what each parameter represents, but doesn't provide format examples (e.g., email format, ID structure) or constraints, leaving gaps in understanding.
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 the shareable link for a Google Drive file or folder.' It specifies the verb ('gets') and resource ('shareable link'), and distinguishes it from siblings like 'get_drive_file_permissions' or 'check_drive_file_public_access' by focusing on link retrieval rather than permissions or access checks. However, it doesn't explicitly differentiate from 'get_drive_file_download_url', which might be a similar sibling tool.
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., not for non-Google Drive files), or comparisons to siblings like 'get_drive_file_download_url' or 'check_drive_file_public_access'. The agent must infer usage from the purpose alone, which is insufficient for optimal 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 full burden for behavioral disclosure. It states this is a 'Get' operation which implies read-only behavior, but doesn't specify authentication requirements, permission levels needed, rate limits, error conditions, or what happens if the response doesn't exist. The description mentions returning 'Response details including answers and metadata' but doesn't elaborate on the structure or completeness of this information.
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 statement, Args, Returns) and uses minimal sentences. The front-loaded purpose statement is clear, and the parameter documentation is organized efficiently. There's no redundant information, though the 'Args:' and 'Returns:' labels could be considered slightly verbose in a pure MCP context.
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 provides adequate but minimal coverage. The presence of an output schema means the description doesn't need to detail return values extensively. However, with no annotations and 0% schema description coverage, the description should ideally provide more behavioral context about authentication, error handling, and relationship to sibling tools to be fully complete.
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 includes an Args section that documents all three parameters with basic explanations, adding value beyond the bare schema. However, it doesn't provide format details (e.g., what constitutes a valid form_id or response_id), examples, or constraints beyond marking them as required. The baseline would be lower without this parameter documentation in the description.
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 'Get one response from the form' - a specific verb+resource combination. It distinguishes itself from the sibling tool 'list_form_responses' by focusing on retrieving a single response rather than listing multiple responses. However, it doesn't explicitly contrast with other form-related tools beyond this implicit 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. While 'list_form_responses' is clearly a sibling tool for listing multiple responses, the description doesn't mention this alternative or provide any context about when retrieval of a single response is appropriate versus listing all responses. There are no usage prerequisites or exclusion criteria 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves details but doesn't cover aspects like authentication requirements (implied by 'user_google_email'), rate limits, error handling, or whether it's a read-only operation. The description is minimal and misses key behavioral traits 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.
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 parameter and return sections. It avoids unnecessary fluff, though the 'Args' and 'Returns' labels are slightly redundant given the structured fields. Every sentence adds value, making it efficient and easy to scan.
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 but lacks behavioral context and usage guidelines. The output schema exists, so the description doesn't need to detail return values, but overall it leaves gaps in transparency and guidance.
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 lists and briefly describes the three parameters, adding meaning beyond the input schema (which has 0% description coverage). However, it doesn't explain parameter formats (e.g., what a 'page_object_id' looks like), sources, or constraints, leaving gaps. With schema coverage low, the description compensates partially but not fully.
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'), resource ('page/slide'), and context ('in a presentation'), making the action unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_presentation' or 'get_page_thumbnail', 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 'get_presentation' (for overall presentation details) or 'get_page_thumbnail' (for visual thumbnails), nor does it specify prerequisites or exclusions. Usage is implied only by the tool's name and description, lacking explicit 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 states the tool 'Gets information' but doesn't clarify if this requires specific permissions, what happens on errors, or if there are rate limits. The description adds 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections for purpose, args, and returns. It's appropriately sized without unnecessary details. However, the 'Args' and 'Returns' sections could be integrated more seamlessly into the flow, slightly affecting structure.
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), the description is somewhat complete but has gaps. It explains the purpose and parameters but lacks behavioral details and usage guidelines. The presence of an output schema reduces the need to detail return values, but overall completeness is adequate with room for improvement.
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 details. The description includes an 'Args' section that documents both parameters with names and types, adding meaningful semantics. However, it doesn't explain format constraints (e.g., valid email patterns or spreadsheet ID structure), 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: 'Gets information about a specific spreadsheet including its sheets.' It specifies the verb ('Gets'), resource ('spreadsheet'), and scope ('including its sheets'). However, it doesn't explicitly differentiate from sibling tools like 'list_spreadsheets' or 'read_sheet_values', 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 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 data from sheets), nor does it specify prerequisites or exclusions. Usage is implied but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 pagination ('Token for retrieving next page of results') and that it returns 'basic details,' but it doesn't specify what 'basic details' include, whether it requires specific permissions (e.g., access to the form), rate limits, or error handling. For a list operation with 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 appropriately sized and front-loaded, starting with the core purpose. The Args and Returns sections are structured clearly, with each sentence adding value by explaining parameters and output. There's no wasted text, making it efficient for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 (list operation with pagination), no annotations, and an output schema exists (implied by 'Returns' section), the description is moderately complete. It covers parameters and output at a high level but lacks behavioral context like permissions or error cases. With output schema handling return values, the description doesn't need to detail them, but it should address usage and behavioral aspects more thoroughly.
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. It adds meaning by explaining each parameter's role: 'user_google_email' as 'The user's Google email address. Required,' 'form_id' as 'The ID of the form,' 'page_size' as 'Maximum number of responses to return. Defaults to 10,' and 'page_token' as 'Token for retrieving next page of results.' This clarifies beyond the bare schema, but it doesn't provide format details (e.g., email validation, form ID structure) 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: 'List a form's responses.' It specifies the verb ('List') and resource ('form's responses'), making it easy to understand what the tool does. However, it doesn't differentiate from sibling tools like 'get_form_response' or 'get_form', which might retrieve individual responses or form metadata, so it doesn't fully distinguish from alternatives.
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_form_response' (which might retrieve a single response) or 'get_form' (which might retrieve form details), leaving the agent to guess based on context. There's no explicit when/when-not or alternative usage advice.
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 lists filters but does not cover critical aspects like authentication requirements, rate limits, pagination, error handling, or whether it's read-only or mutative. The description is insufficient for a tool with no annotation support, leaving 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the main purpose, followed by clear sections for arguments and returns. It uses minimal sentences that directly convey necessary information without redundancy, though the 'Args' and 'Returns' formatting could be slightly more integrated for optimal flow.
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 (one parameter) and the presence of an output schema (which handles return values), the description is somewhat complete but lacks depth. It covers the basic purpose and parameters but misses behavioral details and usage guidelines, making it adequate but with clear gaps for effective agent 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 includes an 'Args' section that documents the single parameter 'user_google_email' with its type and requirement, adding meaning beyond the input schema, which has 0% description coverage. However, it does not explain the parameter's purpose or format (e.g., email validation), and with only one parameter, the baseline is 4, but the lack of deeper semantic context reduces the 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: 'Lists all Gmail filters configured in the user's mailbox.' It specifies the verb ('Lists'), resource ('Gmail filters'), and scope ('all' in 'user's mailbox'), making it easy to understand. However, it does not explicitly differentiate from sibling tools like 'list_gmail_labels' 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. It lacks any mention of prerequisites, context, or comparisons to sibling tools such as 'list_gmail_labels' or 'search_gmail_messages'. This omission leaves the agent without direction on appropriate usage 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool lists labels but doesn't cover aspects like authentication requirements, rate limits, pagination, or error handling. 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.
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, making it easy to parse. It's concise with no redundant information, though the 'Returns' section could be more integrated into the main description for better flow.
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, the description is moderately complete. It covers the basic purpose and parameters but lacks behavioral details and usage context, which are important for a tool with no annotations to guide the agent effectively.
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 documents the single parameter 'user_google_email' as required, adding meaning beyond the input schema's 0% coverage. However, it doesn't explain the parameter's format or constraints, such as whether it must be a valid email or if it supports aliases, limiting its helpfulness.
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 all labels in the user's Gmail account.' It specifies the verb ('Lists') and resource ('labels in the user's Gmail account'), making the action clear. However, it doesn't differentiate from sibling tools like 'manage_gmail_label' or 'list_gmail_filters', 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 siblings like 'search_gmail_messages' or 'get_gmail_message_content', nor does it specify prerequisites or contexts for usage, leaving the agent without explicit 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 mentions the tool can 'write, update, or clear values' and returns a confirmation message, but lacks critical details: it doesn't specify required permissions (e.g., edit access to the sheet), whether changes are reversible, potential rate limits, or error conditions. 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. It starts with a clear purpose statement, followed by a parameter breakdown and return information. Each sentence adds value without redundancy. Minor improvements could include bullet points for parameters, 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?
Given the tool's complexity (6 parameters, mutation operation) and lack of annotations, the description is moderately complete. It covers the purpose, parameters, and return value, and an output schema exists (though not shown), reducing the need to explain returns. However, it misses behavioral context (e.g., permissions, side effects) and usage guidelines, making it adequate but with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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. It provides a brief explanation for each parameter (e.g., '2D array of values to write/update'), which adds meaning beyond the bare schema. However, it doesn't fully detail parameter interactions (e.g., how 'clear_values' affects 'values'), formats (e.g., examples for 'range_name'), or constraints (e.g., valid 'value_input_option' values beyond defaults), leaving 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: 'Modifies values in a specific range of a Google Sheet - can write, update, or clear values.' It specifies the verb ('modifies'), resource ('Google Sheet'), and scope ('specific range'), making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'read_sheet_values' or 'format_sheet_range', 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 'read_sheet_values' for reading data or 'format_sheet_range' for formatting, nor does it specify prerequisites (e.g., authentication, permissions) or 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?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'Read' implies a read-only operation, it doesn't specify whether this requires specific permissions, how comments are returned (format, pagination), what happens with no comments, or any rate limits. The description is minimal and lacks 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.
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 a simple tool and front-loads the core purpose immediately.
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 handles return values), no annotations, and only 2 parameters, the description is minimally complete. However, for a tool that likely requires authentication and returns structured comment data, more context about permissions and behavior would be helpful despite the output schema.
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 mentions 'Google Document' which hints at 'document_id', but doesn't explain what 'user_google_email' is for (authentication, filtering, etc.) or provide any format/validation details. It adds minimal value beyond what's implied by the tool name.
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'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'read_presentation_comments' or 'read_spreadsheet_comments' beyond specifying 'Document' in the resource name.
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 'read_presentation_comments' or 'read_spreadsheet_comments'. It also doesn't mention prerequisites, access requirements, or any 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 the full burden of behavioral disclosure. It states a read operation but doesn't mention any behavioral traits like pagination, rate limits, error handling, or what the output contains. This leaves significant gaps for an agent to understand how the tool behaves beyond its basic function.
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 front-loads the core purpose without unnecessary words. It's appropriately sized for a straightforward tool, with zero waste or redundancy, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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, no nested objects) and the presence of an output schema (which handles return values), the description is minimally adequate. However, with no annotations and 0% schema coverage, it lacks details on authentication, error cases, or parameter semantics, leaving room for improvement in completeness.
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 by explaining parameters, but it adds no meaning beyond what the schema provides. The two required parameters ('user_google_email' and 'presentation_id') are undocumented in both the schema and description, leaving their purpose and format unclear to the agent.
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 target resource ('all comments from a Google Presentation'), making the purpose immediately understandable. It doesn't distinguish from sibling tools like 'read_document_comments' or 'read_spreadsheet_comments', but the specificity to presentations 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 like 'get_presentation' or other comment-related tools. The description lacks context about prerequisites, such as authentication or permissions needed, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 a read operation but doesn't cover critical aspects like authentication needs (implied by 'user_google_email' parameter), rate limits, pagination, error handling, or what the output contains. This leaves significant gaps for a tool that interacts with external APIs.
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 zero waste. It's front-loaded with the core purpose and appropriately sized for a simple tool, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 (external API interaction, 2 required parameters) and the presence of an output schema (which reduces need to describe return values), the description is minimally adequate. However, with no annotations and poor parameter documentation, it lacks completeness for safe and effective use by an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, meaning both parameters are undocumented in the schema. The description adds no information about what 'user_google_email' and 'spreadsheet_id' represent, their formats, or how to obtain them. For a tool with 2 required parameters, this is insufficient compensation 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 ('Read') and resource ('all comments from a Google Spreadsheet'), providing specific verb+resource pairing. However, it doesn't explicitly differentiate from sibling tools like 'read_document_comments' or 'read_presentation_comments' beyond the spreadsheet context, which is why it doesn't reach 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 offers no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context for use, or compare it to related 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 the full burden of behavioral disclosure. It states the action ('Reply to') but doesn't mention required permissions, rate limits, whether replies are editable/deletable, or what the output contains. 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.
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 for the tool's apparent complexity and front-loads the core action clearly.
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 should cover return values), the description's main gaps are in parameter semantics and behavioral context. However, for a mutation tool with 4 parameters and no annotations, the description is minimally adequate but lacks important details about usage and parameters.
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 doesn't explain what 'user_google_email', 'spreadsheet_id', 'comment_id', or 'reply_content' represent or require, failing to compensate for the schema's lack of 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 Spreadsheet'), providing a specific verb+resource combination. 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 about when to use this tool versus alternatives like 'resolve_spreadsheet_comment' or other comment-related tools. The description lacks context about prerequisites, timing, or exclusions, offering only a basic functional 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 the full burden of behavioral disclosure. It states the action ('Resolve') but does not explain what 'resolve' entails (e.g., marking as resolved, deleting, archiving), whether it requires specific permissions, or what the outcome looks like. 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 that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, with zero waste, making it easy to parse 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 the tool's moderate complexity (a mutation with 3 parameters) and the presence of an output schema (which reduces the need to describe return values), the description is minimally adequate. However, with no annotations and 0% schema coverage, it lacks crucial details about behavior and parameters, making it incomplete for safe and 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?
The schema description coverage is 0%, meaning none of the three parameters (user_google_email, presentation_id, comment_id) are documented in the schema. The description does not add any meaning beyond the parameter names, failing to explain what these inputs represent or their expected formats, leaving them entirely undocumented.
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 resource ('a comment in a Google Presentation'), making the purpose immediately understandable. However, it does not differentiate this tool from its sibling 'resolve_document_comment' or 'resolve_spreadsheet_comment', which perform similar actions on different Google Workspace resources, missing an opportunity for explicit 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 like 'reply_to_presentation_comment' or other comment-related tools. It lacks context about prerequisites, such as needing an existing comment to resolve, or exclusions, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 creates a new form, implying a write/mutation operation, but doesn't mention required permissions, rate limits, side effects, or whether the form is immediately published. The return format is documented, but other behavioral aspects are missing.
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 organized sections for Args and Returns. It's appropriately sized with no redundant information. The only minor improvement would be integrating the parameter explanations more seamlessly rather than as a separate 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 creation tool with no annotations and 4 parameters, the description covers the basic operation and parameters adequately. The output schema exists, so the description doesn't need to detail return values. However, it lacks context about authentication requirements, error conditions, or how this tool relates to other form management tools.
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 and 4 parameters, the description adds significant value by explaining each parameter's purpose: 'user_google_email' identifies the user, 'title' sets the form title, 'description' provides optional details, and 'document_title' sets the browser tab title. This compensates well for the schema's lack of descriptions, though it doesn't specify format constraints or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool creates a new form with a specific title from the request. It specifies the verb ('Create') and resource ('new form'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'create_doc' or 'create_spreadsheet' beyond the form 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 (like authentication or permissions), compare it to similar tools (like 'create_doc' or 'create_spreadsheet'), or specify when this tool is appropriate versus other form-related tools like 'get_form'.
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 that the tool creates a new presentation but doesn't specify whether this requires write permissions, how errors are handled, or any rate limits. The return format is briefly described, but behavioral traits like side effects or authentication needs 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 for Args and Returns, making it easy to parse. It's concise with no redundant information, though the front-loading could be improved by integrating the return details 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 moderate complexity (2 parameters, no annotations, but with an output schema), the description is adequate but incomplete. It covers the basic purpose and parameters but lacks usage context, error handling, and authentication details, which are important for a creation tool in a Google ecosystem.
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 both parameters: it explains that user_google_email is required and specifies the default value for title. Since schema description coverage is 0%, this compensates well by clarifying parameter roles, though it doesn't detail format constraints like 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 'Create' and resource 'Google Slides presentation', making the purpose specific and understandable. It distinguishes from siblings like 'create_doc' or 'create_sheet' by specifying the presentation type, though it doesn't explicitly contrast with them.
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 lacks context about prerequisites, such as whether the user needs specific permissions or authentication, which is critical given the 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. While it states this is a creation operation (implying mutation), it doesn't address critical aspects like required permissions, whether the operation is idempotent, error conditions, or rate limits. 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 clear sections (purpose, Args, Returns) and uses minimal sentences. Each section earns its place by providing necessary information without redundancy. The only minor improvement would be integrating the purpose statement more seamlessly with the parameter explanations.
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 (creation operation with 3 parameters), no annotations, and an output schema that only specifies return type (not content), the description is adequate but incomplete. It covers the basic operation and parameters but lacks behavioral context, error handling, and detailed output information that would be helpful for an 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?
With 0% schema description coverage, the description provides essential semantic context for all three parameters through the Args section, explaining what each parameter represents. This significantly compensates for the lack of schema descriptions, though it doesn't provide format details (e.g., email validation, ID patterns) or constraints beyond basic requirements.
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 ('Creates') and resource ('new sheet within an existing spreadsheet'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'create_spreadsheet' (which creates entire spreadsheets rather than sheets within them), though the distinction is implied by the description's wording.
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), compare it to similar tools like 'create_spreadsheet', or specify scenarios where this operation is appropriate versus other sheet-related 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?
With no annotations provided, the description carries full burden but offers limited behavioral insight. It mentions the tool creates a new spreadsheet and returns information, but doesn't disclose permissions needed, rate limits, whether it's idempotent, or error conditions. The return format is briefly described, but more context on behavior is missing.
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. The Args and Returns sections are structured clearly, though the initial sentence is somewhat redundant with the tool name. Every sentence adds value, making it efficient overall.
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 somewhat complete. It covers parameters and return values, but lacks context on authentication, error handling, or sibling tool differentiation. The output schema exists, so detailed return explanation isn't needed, but overall completeness is adequate with 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?
The description adds significant meaning beyond the input schema, which has 0% description coverage. It explains that 'user_google_email' is the user's Google email address, 'title' is the spreadsheet title, and 'sheet_names' is an optional list for custom sheet names with a default behavior. 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 creates a new Google Spreadsheet, specifying the verb 'creates' and resource 'Google Spreadsheet'. It distinguishes from siblings like 'create_doc' or 'create_presentation' by specifying spreadsheet creation, though it doesn't explicitly contrast with 'create_sheet' which might be similar.
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 (like authentication), compare with sibling tools (e.g., 'create_sheet' or 'create_drive_file'), or specify use cases beyond the basic creation action.
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 tool 'inserts' elements, implying a write operation, but doesn't disclose behavioral traits like required permissions, whether changes are reversible, error handling, or rate limits. The return value is mentioned but without details on success/failure cases. 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. It starts with a clear purpose statement, followed by organized sections for Args and Returns. Each sentence earns its place by conveying essential information. Minor verbosity in parameter explanations keeps it from a perfect score, 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?
Given the tool's complexity (8 parameters, mutation operation) and lack of annotations, the description is moderately complete. It explains parameters well and mentions a return value, but lacks behavioral context (e.g., side effects, error cases). The output schema exists, so return details aren't needed, but for a write tool with no annotations, more operational guidance 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 provides clear semantics for all 8 parameters in the 'Args' section, explaining what each represents (e.g., 'user_google_email: User's Google email address') and conditional requirements (e.g., 'rows: Number of rows for table (required for table)'). This adds significant value beyond the bare schema, though it doesn't cover validation rules or examples.
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: 'Inserts structural elements like tables, lists, or page breaks into a Google Doc.' It specifies the verb ('inserts') and resource ('Google Doc'), and lists the types of elements. However, it doesn't explicitly differentiate from sibling tools like 'insert_doc_image' or 'modify_doc_text', 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 prerequisites (e.g., document access), compare to similar tools (e.g., 'batch_update_doc' for bulk operations), or specify scenarios where it's appropriate. Usage is implied through parameter descriptions but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 states the action ('Inserts'), it doesn't mention permission requirements, whether the operation is idempotent, error conditions (e.g., invalid image formats, permission denied), or what happens if width/height are omitted (default behavior implied but not stated). The confirmation message return is mentioned but without detail on format or 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?
The description is well-structured with a clear purpose statement followed by organized parameter and return value sections. Each sentence earns its place by providing essential information. It could be slightly more concise by integrating the parameter explanations into the main description rather than a separate 'Args:' section, but overall it's efficient and readable.
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 (implied by 'Returns' statement), the description does an adequate job. It covers the basic operation and parameters but lacks important context: no error handling information, no mention of Google Docs API limitations (size, rate limits), and no guidance on authentication requirements despite the user_google_email parameter. The output schema reduces but doesn't eliminate the need for behavioral 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?
Schema description coverage is 0%, so the description must compensate. It provides clear semantic explanations for all 6 parameters: identifies 'user_google_email' as authentication context, 'document_id' as target, 'image_source' options (Drive file ID or URL), 'index' as 0-based position, and optional width/height in points. This adds substantial value beyond the bare schema, though it doesn't explain format constraints (e.g., URL must be public) or edge cases.
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 an image') and target resource ('into a Google Doc'), specifying the source options ('from Drive or a URL'). It distinguishes itself from siblings like 'modify_doc_text' or 'insert_doc_elements' by focusing specifically on image insertion. However, it doesn't explicitly contrast with other document modification tools beyond the title-level 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 like 'insert_doc_elements' (which might handle other element types) or 'batch_update_doc' (which might handle multiple updates). There's no mention of prerequisites, constraints, or typical use cases beyond the basic functionality 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves data (implying read-only) and mentions authentication context, but lacks details on rate limits, pagination, error handling, or what happens if the email is invalid. For a tool with no annotations, this is insufficient to fully inform the agent about 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 well-structured and appropriately sized. It front-loads the purpose in the first sentence, followed by clear sections for arguments and returns. There is no wasted text, making it efficient for quick understanding, though minor improvements in detail could enhance it further.
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 low complexity (one parameter) and the presence of an output schema (implied by the Returns section), the description is reasonably complete. It covers the purpose, input, and output, but lacks behavioral details and usage guidelines, which are partially mitigated by the structured return information.
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 adds minimal semantics beyond the input schema. It specifies that 'user_google_email' is required and describes it as 'The user's Google email address,' but the schema already indicates it's a required string. With 0% schema description coverage, the description does not compensate by explaining format constraints or usage context, resulting in 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: 'Retrieves a list of calendars accessible to the authenticated user.' It specifies the verb ('retrieves'), resource ('calendars'), and scope ('accessible to the authenticated user'). However, it does not explicitly differentiate from sibling tools like 'get_events' or 'list_drive_items', which prevents 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 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 mentions the tool's function but does not specify prerequisites, exclusions, or comparisons to sibling tools like 'get_events' or other list operations. This lack of contextual usage information 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. It states the tool lists spreadsheets, implying a read-only operation, but doesn't clarify aspects like authentication requirements, rate limits, pagination, or error handling. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior and constraints.
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 sections for arguments and returns. Each sentence adds value, and there's no redundant information. It could be slightly more concise by integrating the sections more fluidly, 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 that there are no annotations and an output schema exists (implied by 'Returns' section), the description is moderately complete. It covers the purpose and parameters adequately, but lacks behavioral context like authentication or error handling. For a simple list tool, this might be sufficient, but the absence of annotations means more detail would be helpful for reliable 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 documents both parameters: 'user_google_email' and 'max_results', with details on data types, requirements, and defaults. Since the schema description coverage is 0%, this adds substantial value beyond the bare schema, explaining what each parameter means and how to use them. However, it doesn't cover edge cases or validation rules, so it's not a perfect 5.
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 specifies the verb ('Lists'), resource ('spreadsheets'), and scope ('from Google Drive that the user has access to'). However, it doesn't explicitly distinguish this tool from sibling tools like 'list_drive_items' or 'search_drive_files', which might also list files, 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 'list_drive_items' or 'search_drive_files', nor does it specify any prerequisites or exclusions. The agent must infer usage from the tool name and description alone, which is insufficient for optimal 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 an update operation but doesn't mention permission requirements, whether changes are reversible, rate limits, or what happens to existing publish settings not mentioned. The confirmation message return is noted, but behavioral context is minimal.
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 Args and Returns sections. It's appropriately sized with no redundant information, though the 'Args' and 'Returns' labels are slightly verbose compared to integrating this information 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 (4 parameters, mutation operation), no annotations, and an output schema present (implied by the Returns section), the description is moderately complete. It covers parameters well and notes the return type, but lacks behavioral context like error conditions or side effects, which is a gap 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?
The description adds significant value beyond the schema, which has 0% description coverage. It explains each parameter's purpose (e.g., 'user_google_email' as 'The user's Google email address'), default values, and required status. This compensates well for the schema's lack of descriptions, though it doesn't 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 tool's purpose as 'Updates the publish settings of a form' with a specific verb ('Updates') and resource ('publish settings of a form'). It distinguishes from siblings like 'create_form' or 'get_form' by focusing on publish settings updates, though it doesn't explicitly differentiate from similar update tools like 'update_drive_file'.
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), when not to use it, or how it differs from other form-related tools like 'create_form' or 'get_form_response' 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?
With no annotations provided, the description carries full burden for behavioral disclosure. While it mentions that 'changing type may require content upload' for mime_type, it doesn't cover important behavioral aspects like authentication requirements, permission levels needed, whether updates are reversible, rate limits, or what happens when multiple parameters are modified simultaneously. For a mutation tool with 12 parameters, 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 efficiently organized. The Args section is comprehensive but necessary given the parameter count. The opening sentence clearly states the purpose, though the detailed parameter explanations are appropriately placed after the high-level 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 12 parameters and no annotations, the description does well on parameter documentation and includes a Returns section. However, it lacks important context about behavioral aspects (permissions, side effects, error conditions) and doesn't provide usage guidance relative to sibling tools. The presence of an output schema helps, but more behavioral context would be needed for full 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?
With 0% schema description coverage, the description provides excellent parameter semantics by explaining each of the 12 parameters in the Args section. It adds meaningful context beyond the schema, such as the note about mime_type changes potentially requiring content upload, and clarifies that add_parents/remove_parents accept comma-separated folder IDs. 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 tool's purpose as 'Updates metadata and properties of a Google Drive file,' which is a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'update_doc_headers_footers' or 'modify_sheet_values,' which also perform updates 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 on when to use this tool versus alternatives. With many sibling tools performing various update operations (e.g., update_doc_headers_footers, modify_sheet_values, modify_event), there's no indication of when this specific Drive file update tool is appropriate versus other update tools in the server.
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 states this is a 'Get' operation (implying read-only), it doesn't explicitly confirm this is non-destructive. It also doesn't mention rate limits, authentication requirements, error conditions, or what happens with invalid inputs. The description adds 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 well-structured and appropriately sized. It begins with a clear purpose statement, followed by organized sections for Args and Returns. Each sentence earns its place by providing essential information without redundancy. The formatting with clear section headers 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?
For a read-only tool with 2 parameters and an output schema, the description is minimally adequate. It covers the basic purpose and parameters but lacks important context like authentication requirements, error handling, or when to use versus alternatives. The presence of an output schema means the description doesn't need to detail return values, but it could provide more behavioral context given the lack of annotations.
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 clear semantics: 'user_google_email (str): The user's Google email address. Required.' and 'presentation_id (str): The ID of the presentation to retrieve.' With 0% schema description coverage, the description fully compensates by providing complete parameter documentation, including purpose and requirement status for both parameters.
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 as 'Get details about a Google Slides presentation' with specific verb ('Get') and resource ('Google Slides presentation'). It distinguishes from siblings like 'get_doc_content' or 'get_spreadsheet_info' by specifying the presentation resource type. However, it doesn't explicitly differentiate from potential presentation-related siblings like 'get_presentation_comment' or 'batch_update_presentation'.
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 when this tool is appropriate compared to other presentation tools like 'create_presentation', 'batch_update_presentation', or 'get_presentation_comment'. There's also no information about prerequisites, authentication requirements, or access permissions needed.
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 implies a mutation ('Updates'), it doesn't specify required permissions, whether changes are reversible, rate limits, or error handling. The description adds minimal behavioral context beyond the basic action, which is 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded: it starts with a clear purpose statement, followed by organized sections for Args and Returns. Every sentence earns its place, with no redundant information, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 parameters and return values, and an output schema exists, so it doesn't need to explain returns in detail. However, it lacks behavioral details like permissions or error handling, which are crucial for a mutation tool without annotations.
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 5 parameters with brief explanations, such as 'User's Google email address' for 'user_google_email' and 'Text content for the header/footer' for 'content'. Since schema description coverage is 0%, this compensates well by adding semantic meaning beyond the bare schema, though it could provide more detail on enum values 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 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 'modify_doc_text' or 'batch_update_doc', which could also modify document content, so it doesn't reach 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 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 'modify_doc_text' for general text changes or 'batch_update_doc' for bulk updates, nor does it specify prerequisites or exclusions. 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions the tool modifies an existing event (implying mutation) and describes the return value, it lacks critical behavioral details: required permissions (e.g., calendar write access), whether modifications are reversible, error handling (e.g., invalid event_id), rate limits, or side effects. The description adds some context (e.g., format examples for parameters) but is 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately front-loaded with the core purpose, but it's lengthy due to detailed parameter documentation. While this detail is necessary given the schema coverage gap, some sentences could be more concise (e.g., repetitive 'If None, preserves existing...' patterns). The structure (purpose, args, returns) is clear, but the bulkiness slightly reduces efficiency.
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 (15 parameters, mutation operation, no annotations) and the presence of an output schema (returns a confirmation string), the description is largely complete. It thoroughly documents all parameters and the return value. However, it lacks behavioral context (e.g., permissions, errors) that would be crucial for safe invocation, preventing a perfect score.
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 semantic information for all 15 parameters. It explains each parameter's purpose (e.g., 'user_google_email: The user's Google email address. Required.'), format requirements (e.g., RFC3339 for time fields), default values (e.g., calendar_id default: 'primary'), constraints (e.g., max 5 reminders), and behavioral effects (e.g., 'If None, preserves existing color.'). This goes far 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 tool's purpose: 'Modifies an existing event.' This is a specific verb+resource combination that distinguishes it from sibling tools like 'create_event' and 'delete_event'. However, it doesn't explicitly differentiate itself from other modification tools in the sibling list, such as 'modify_doc_text' or 'modify_sheet_values', 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 an existing event), compare it to 'create_event' for new events, or specify scenarios where it's appropriate. The only implied usage is modifying events, but no explicit context or exclusions are provided.
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 operation without disclosing behavioral traits. It doesn't mention permissions needed, whether changes are reversible, rate limits, or error handling, leaving 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.
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 part adds value, though the 'Args' formatting could be more integrated rather than bullet-like for optimal flow.
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, 0% schema coverage, but an output schema exists, the description is partially complete. It covers parameters and return value basics but lacks behavioral context (e.g., safety, side effects) that annotations would typically provide.
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's 'Args' section clearly documents all 5 parameters with meaningful names and brief explanations (e.g., 'Text to search for', 'Whether to match case exactly'). This compensates well for the schema gap, though it lacks format examples.
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 ('Finds and replaces text') and resource ('throughout a Google Doc'), distinguishing it from siblings like 'modify_doc_text' or 'batch_update_doc'. It precisely communicates the tool's function without redundancy.
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_doc_text' or 'batch_update_doc'. The description lacks context about prerequisites, constraints, or typical use cases, offering only basic functional information.
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 but doesn't mention authentication requirements, rate limits, error conditions, or whether this is a read-only operation (though implied by 'retrieves'). For a tool accessing user data 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 a clear purpose statement followed by Args and Returns sections. Every sentence adds value, though the formatting note ('formatted for reading') could be more specific. It's appropriately sized for a 2-parameter 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 moderate complexity (retrieving threaded email data), no annotations, and an output schema present (which handles return values), the description is minimally adequate. It covers purpose and parameters but lacks behavioral context and usage guidance, leaving room for improvement.
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 clearly explains both parameters: 'thread_id' is 'the unique ID of the Gmail thread to retrieve' and 'user_google_email' is 'the user's Google email address' and 'required'. This adds essential meaning beyond the bare schema, though it doesn't specify 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 ('complete content of a Gmail conversation thread'), and scope ('including all messages'). It distinguishes this tool from sibling tools like 'get_gmail_message_content' (single message) and 'get_gmail_threads_content_batch' (batch operation).
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 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 appropriate contexts for use.
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 that the tool retrieves content via different APIs depending on file type and returns a string with metadata header, which adds useful behavioral context. However, it lacks details on permissions, rate limits, or error handling, leaving gaps for a tool with two 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 with bullet points and a clear returns section, making it easy to scan. It avoids unnecessary fluff, but the bullet points could be more concise, and the metadata header detail might be better placed in an output schema context.
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, the description does not need to detail return values, which it handles adequately. However, with no annotations, 0% schema coverage, and two required parameters, the description lacks sufficient context on authentication, error cases, and parameter usage, making it incomplete for safe and 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. It mentions document_id in the context of identifying files but does not explain user_google_email or provide any details on parameter formats, constraints, or examples. This leaves both parameters largely undocumented beyond their names.
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 retrieves content from Google Docs or Drive files, specifying both native Google Docs and Office files like .docx. It distinguishes from siblings like get_drive_file_content by explicitly mentioning the dual API approach and metadata header in returns.
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 document content but does not explicitly state when to use this tool versus alternatives like get_drive_file_content or inspect_doc_structure. No exclusions or prerequisites are mentioned, leaving usage context inferred rather than guided.
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 (URL) but lacks critical details: whether this requires specific permissions, if the URL is ephemeral or persistent, rate limits, error conditions (e.g., invalid page ID), or if it triggers external API calls. For a tool generating URLs with user credentials, 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 core purpose, followed by a clear Args/Returns breakdown. Every sentence adds value—no fluff or repetition. It efficiently communicates essential information in minimal space.
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 has output schema), the description is partially complete. It covers parameters and return type adequately, but lacks behavioral context (e.g., permissions, URL lifespan). The output schema reduces the need to detail return values, but gaps in usage and transparency 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 effectively explains all 4 parameters: user_google_email clarifies it's for authentication, presentation_id and page_object_id specify the target, and thumbnail_size defines options with defaults. However, it doesn't detail format constraints (e.g., ID structure) or enum values beyond size examples, leaving minor gaps.
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 target resource ('for a specific page (slide) in a presentation'), distinguishing it from sibling tools like get_presentation or get_page which retrieve different content. It precisely communicates the tool's function without ambiguity.
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 it to similar tools like get_drive_file_download_url, or specify use cases (e.g., embedding thumbnails in reports). 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 the full burden of behavioral disclosure. While it mentions the three actions and some parameter requirements, it doesn't disclose important behavioral traits like authentication requirements, permission levels needed, whether operations are reversible, rate limits, or error conditions. The return value description is minimal ('Confirmation message'), lacking detail about success/failure formats.
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 bullet-like formatting. It's appropriately sized for a 6-parameter tool with multiple actions. Minor improvement could be made by front-loading more critical information about parameter dependencies, but overall it's efficient and organized.
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, no annotations, and 0% schema description coverage, the description provides good parameter documentation but lacks important context. While it has an output schema (returns str), it doesn't fully address behavioral aspects like authentication, permissions, or error handling. The description does a decent job given the complexity but has clear gaps in 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 description provides excellent parameter semantics beyond the schema. With 0% schema description coverage, the description fully compensates by explaining each parameter's purpose, requirements, and constraints. It clarifies which parameters are required for which actions, provides enum meanings, and adds contextual information not present in 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 as managing Gmail labels through create, update, or delete operations. It specifies the resource (Gmail labels) and the three possible actions. However, it doesn't explicitly distinguish this tool from sibling tools like 'list_gmail_labels' or 'modify_gmail_message_labels', 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage through the parameter documentation (e.g., 'Required for create, optional for update'), but doesn't provide explicit guidance on when to use this tool versus alternatives. There's no mention of when to choose create vs. update vs. delete, or how this differs from sibling tools like 'list_gmail_labels' or 'batch_modify_gmail_message_labels'.
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 tool can 'modify text' and 'apply formatting', implying mutation, but lacks details on permissions required, error conditions (e.g., invalid indices), rate limits, or whether changes are reversible. The description adds 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.
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. It avoids redundancy, though the parameter list is lengthy due to the tool's complexity. Every sentence adds value, but the bulk of text is necessary for parameter clarity given the low schema coverage.
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 12 parameters, no annotations, and 0% schema coverage, the description does well on parameters but lacks behavioral context (e.g., error handling, auth needs). The output schema exists (returns a confirmation string), so return values need not be explained, but overall completeness is moderate due to missing usage and transparency details.
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 provides detailed explanations for all 12 parameters, including optionality (e.g., 'optional - can format existing text without changing it'), default behaviors (e.g., 'if not provided with text, text is inserted'), and examples (e.g., font family names). This adds significant 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 ('modifies', 'insert/replace text', 'apply formatting') and resource ('Google Doc'), distinguishing it from siblings like 'find_and_replace_doc' (which likely does only replacement) or 'batch_update_doc' (which handles multiple operations). It explicitly mentions the single-operation capability, which is a key differentiator.
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 'find_and_replace_doc' or 'batch_update_doc', nor does it mention prerequisites (e.g., document access permissions) or contextual constraints. Usage is implied through parameter descriptions but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 that gradient_points 'creates a gradient rule' and overrides other parameters, which is useful behavioral context. However, it doesn't disclose important traits like required permissions, whether this is a destructive/mutating operation, rate limits, or error conditions for a tool with 9 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 clear sections (Args, Returns) and front-loaded purpose statement. Most sentences earn their place by explaining parameter behaviors, though some explanations could be more concise. The gradient_points explanation is particularly dense but necessary.
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 complex 9-parameter mutation tool with no annotations, the description provides good parameter semantics and output clarification. However, it lacks important contextual information about authentication requirements, error handling, and the tool's mutating nature. The presence of an output schema helps with return values, but behavioral context remains incomplete.
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 substantial parameter semantics beyond the schema. It explains each parameter's purpose, gives examples for condition_type, clarifies data formats for condition_values and gradient_points, and describes interactions between parameters (gradient_points overriding others). 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 ('Adds a conditional formatting rule') and target resource ('to a range'), distinguishing it from sibling tools like 'delete_conditional_formatting' and 'update_conditional_formatting' that handle different operations on the same 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through parameter explanations (e.g., 'If provided, a gradient rule is created and boolean parameters are ignored'), but doesn't explicitly state when to use this tool versus alternatives like 'format_sheet_range' or 'update_conditional_formatting'. No explicit when-not-to-use guidance is provided.
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 mentions the action ('Exports... and saves') implying a write operation, but does not specify permissions needed, rate limits, or error conditions. The return statement adds some context about confirmation details, but lacks depth on side effects or constraints.
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 front-loaded with the core purpose in the first sentence, followed by structured Arg and Return sections. Each sentence earns its place by clarifying parameters and outcomes, but the optional parameter explanations could be slightly more concise (e.g., combining default behaviors).
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 (export with save), no annotations, and an output schema present (returns a string), the description is reasonably complete. It covers the action, all parameters with semantics, and the return type, though it could improve by mentioning authentication needs or potential failures to fully compensate for missing annotations.
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 four parameters: 'user_google_email' identifies the user, 'document_id' specifies the Doc, 'pdf_filename' explains naming defaults, and 'folder_id' indicates save location. This adds meaningful context beyond the bare schema types, though it could detail format requirements (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 ('Exports a Google Doc to PDF format') and the resource involved ('Google Doc'), distinguishing it from siblings like 'get_doc_content' or 'create_doc'. It explicitly mentions saving to Google Drive, which clarifies the output destination beyond just conversion.
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_download_url' for accessing files or 'update_drive_file' for modifications. It lacks context about prerequisites (e.g., document accessibility) or exclusions, offering only basic functional intent without comparative usage advice.
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 return format (base64-encoded content) but doesn't address important behavioral aspects like authentication requirements (beyond the user_google_email parameter), rate limits, file size limitations, or whether this is a read-only operation. The description provides basic output information but misses key 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.
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 Args and Returns sections. The first sentence efficiently states the core functionality. While the parameter documentation is necessary given the schema coverage gap, the overall structure is clean and front-loaded.
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 (3 parameters, no annotations, but with output schema), the description provides a solid foundation. The output schema handles return value documentation, so the description appropriately focuses on purpose and parameters. For a download operation with authentication requirements, it could benefit from more behavioral context, but it covers the essentials 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?
With 0% schema description coverage, the description must compensate for the lack of parameter documentation. It provides clear semantic meaning for all three parameters: message_id identifies the containing message, attachment_id identifies the specific attachment, and user_google_email specifies whose account to access. 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 specific action ('Downloads the content'), target resource ('a specific email attachment'), and scope ('of a specific email attachment'). It distinguishes itself from siblings like 'get_gmail_message_content' by focusing specifically on attachments rather than full messages.
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 when you need attachment content rather than just message metadata, but doesn't explicitly state when to use this vs alternatives like 'get_gmail_message_content' or 'get_gmail_messages_content_batch'. No explicit exclusions or prerequisites are mentioned 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 creation action and return format, but doesn't mention authentication requirements, rate limits, error conditions, or what happens with duplicate events. It provides basic operational context but lacks comprehensive 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 (Args, Returns) and efficiently documents 14 parameters. While comprehensive, it maintains focus without unnecessary elaboration, though some parameter explanations could be slightly more concise.
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 (14 parameters, 0% schema coverage, no annotations), the description provides substantial context through detailed parameter documentation and return format explanation. The output schema exists, so the description appropriately focuses on input parameters and operational context rather than return values.
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 including data types, formats (RFC3339), examples, constraints (max 5 reminders), defaults, and clear explanations of what each parameter controls. This adds substantial 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 specific action ('Creates a new event') and resource ('event'), distinguishing it from sibling tools like 'modify_event' or 'delete_event'. It provides a complete functional overview of 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 'modify_event' or 'get_events'. The description lacks context about prerequisites, permissions needed, or typical use cases for event creation versus modification.
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 it mentions that omitting certain parameters preserves existing values and describes the return value, it doesn't address important behavioral aspects like whether this requires specific permissions, whether changes are reversible, potential rate limits, or error conditions. The description provides basic operational context but lacks comprehensive behavioral transparency 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 detailed parameter explanations and return value information. While comprehensive, it's appropriately sized for a tool with 10 parameters. The information is front-loaded with the core purpose, though the parameter details are extensive but necessary given the complexity.
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 10 parameters, 0% schema description coverage, no annotations, but with an output schema, the description provides good completeness. It explains the tool's purpose, detailed parameter semantics, and mentions the return value. The main gap is lack of behavioral context around permissions, reversibility, and error handling, but the parameter coverage is excellent and the output schema handles return values.
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 and 10 parameters (7 optional), the description provides excellent parameter semantics. It clearly explains what each parameter does, including specific details like 'A1-style range', '0-based index', 'Hex background color', 'Sheets condition type', and how omitted parameters preserve existing values. 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.
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 ('Updates an existing conditional formatting rule by index on a sheet'), identifies the resource (conditional formatting rule on a sheet), and distinguishes it from sibling tools like 'add_conditional_formatting' and 'delete_conditional_formatting' by specifying it updates existing rules rather than creating or deleting them.
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 it updates existing rules by index, which suggests it should be used when you have an existing rule to modify rather than creating a new one. However, it doesn't explicitly state when to use this versus alternatives like 'add_conditional_formatting' or provide any exclusion criteria or 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 that the tool creates files (a write operation) and mentions support for shared drives, but lacks details on permissions required, rate limits, error handling, or whether the operation is idempotent. It adds some context but is 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.
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 organized Args and Returns sections. It is appropriately sized but could be slightly more concise by integrating some details into the opening sentence. Every sentence 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?
Given the tool's complexity (6 parameters, mutation operation) and no annotations, the description does well by covering parameters thoroughly and including a Returns section. However, with an output schema present, the return value explanation is somewhat redundant, and more behavioral context (e.g., auth needs, error cases) would improve completeness for a write tool.
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 provides detailed semantics for all 6 parameters: explains required vs. optional, default values (e.g., folder_id defaults to 'root'), constraints (e.g., folder_id must be within shared drive for shared drives), and usage (e.g., content vs. fileUrl options with supported protocols). 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 verb 'creates' and resource 'new file in Google Drive', specifying support for shared drives. It distinguishes from sibling tools like 'create_doc', 'create_sheet', etc., which create specific file types, whereas this tool creates general files with content or URLs.
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 mentioning support for shared drives and content/fileUrl options, but does not explicitly state when to use this tool versus alternatives like 'create_doc' for documents or 'update_drive_file' for modifications. No explicit exclusions or prerequisites are provided.
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, the description carries full burden. It discloses the retrieval action and return format, but lacks details on authentication requirements, rate limits, error conditions, or whether it's read-only (implied but not stated). It adds some behavioral context but leaves 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 efficiently structured with a clear purpose statement, followed by Args and Returns sections. Every sentence adds value with no redundancy. It's appropriately sized for a 2-parameter retrieval tool.
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 no annotations, the description does well by explaining parameters and return format. The output schema exists, so return values needn't be detailed. However, it could better address behavioral aspects 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?
Schema description coverage is 0%, so the description must compensate. It explains both parameters: 'message_id' as 'unique ID of the Gmail message to retrieve' and 'user_google_email' as 'user's Google email address. Required.' This adds clear 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'), target resource ('full content of a specific Gmail message'), and scope ('subject, sender, recipients, 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 when needing detailed content of a single message, but doesn't explicitly state when to use this vs. alternatives like batch retrieval or thread-level tools. No guidance on prerequisites or exclusions is provided.
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 read operation ('Reads values'), which is helpful, but doesn't mention authentication requirements, rate limits, error conditions, or what happens with invalid ranges. It adds some context but leaves significant behavioral aspects unspecified.
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 purpose statement. While efficient, the parameter explanations could be slightly more concise, and the Returns section repeats 'formatted values' without fully explaining the output format beyond the string type.
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, read operation) and the presence of an output schema (though not shown in context), the description provides good coverage. It explains all parameters thoroughly and states the return type, though additional context about authentication or error handling would make it more complete for a tool with no 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?
With 0% schema description coverage, the description fully compensates by providing detailed parameter documentation in the Args section. Each parameter is clearly explained with examples (e.g., 'Sheet1!A1:D10'), default values, and enum descriptions. This adds substantial meaning beyond what the bare schema provides.
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 ('Reads values') and resource ('from a specific range in a Google Sheet'), distinguishing it from sibling tools like 'get_spreadsheet_info' or 'modify_sheet_values'. It precisely defines the tool's scope as reading values rather than metadata or performing modifications.
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 what the tool does, but doesn't explicitly state when to use it versus alternatives like 'get_spreadsheet_info' for metadata or 'modify_sheet_values' for writing. It provides context about reading ranges but lacks explicit guidance on tool selection 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?
With no annotations provided, the description carries full burden. It discloses the batch nature and label modification behavior, but doesn't mention important aspects like whether this requires specific Gmail permissions, what happens if message_ids are invalid, whether changes are atomic, or any rate limits. The description adds some behavioral context 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?
The description is well-structured with a clear purpose statement followed by organized parameter and return value sections. While efficient, the Args section could be slightly more concise by integrating parameter descriptions into the main text rather than separate bullet points.
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 batch modification tool with no annotations but with output schema (implied by Returns section), the description provides good coverage. It explains the tool's purpose, parameters, and return value. However, it lacks information about error conditions, authentication requirements, and batch size limitations that would be important for safe usage.
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 50% schema description coverage (only add_label_ids and remove_label_ids have descriptions), the description compensates well by providing clear parameter documentation in the Args section. It explains all four parameters with their types and purposes, adding meaningful context beyond what the bare schema provides for user_google_email and message_ids.
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'), resource ('multiple Gmail messages'), and scope ('in a single batch request'). It distinguishes from the sibling tool 'modify_gmail_message_labels' by emphasizing batch processing rather than single-message modification.
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 implies usage context through 'batch request' and the parameter descriptions suggest when to use add_label_ids vs remove_label_ids. However, it doesn't explicitly state when to choose this tool over the single-message sibling 'modify_gmail_message_labels' or mention any prerequisites like authentication requirements.
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 states this is a deletion operation (implying mutation/destructive action), it doesn't disclose important behavioral traits like permission requirements, whether the deletion is permanent/reversible, error handling for invalid indices, or rate limits. The description adds 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 perfectly structured and front-loaded: the first sentence states the core purpose, followed by well-organized Args and Returns sections. Every sentence earns its place by providing essential information without redundancy. The formatting with clear section headers enhances 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 complexity (destructive operation with 4 parameters), no annotations, and 0% schema coverage, the description does well by documenting all parameters and return values. However, it could provide more context about authentication requirements, error conditions, or the format of the returned 'current rule state'. The presence of an output schema helps but doesn't fully compensate for missing behavioral details.
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 in the Args section. Each parameter is clearly explained with its purpose, data type, required status, and default behavior (e.g., 'Defaults to the first sheet if not provided' for sheet_name). 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 ('Deletes'), target resource ('an existing conditional formatting rule by index on a sheet'), and distinguishes from sibling tools like 'add_conditional_formatting' and 'update_conditional_formatting'. It precisely defines what the tool does without being tautological.
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 (to delete conditional formatting rules by index) and implicitly distinguishes it from sibling tools like 'add_conditional_formatting' and 'update_conditional_formatting'. However, it doesn't explicitly state when NOT to use it or mention alternative approaches for rule deletion.
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 drafts (implying a write operation) and mentions the return value ('Confirmation message with the created draft's ID'), adding some behavioral context. However, it lacks details on permissions, rate limits, error handling, or whether drafts are saved automatically, 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear opening sentence, an 'Args' section listing parameters, a 'Returns' statement, and multiple examples. It is appropriately sized for a 10-parameter tool, but the extensive examples (5 cases) might be slightly verbose, though they earn their place by illustrating usage scenarios effectively.
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 (10 parameters, mutation tool) and no annotations, the description is fairly complete: it explains purpose, parameters, return value, and provides examples. However, it lacks details on authentication needs, error cases, or draft lifecycle (e.g., auto-save behavior), which would enhance completeness for a Gmail integration 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 high (90%), so the baseline is 3. The description adds value by explaining parameter roles beyond the schema: it clarifies that 'to' can be 'left empty for drafts', distinguishes 'thread_id' for 'reply drafts', and notes that 'in_reply_to' and 'references' are for 'proper threading'. This enhances understanding without repeating schema 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 tool 'creates a draft email in the user's Gmail account' with specific verbs ('creates', 'draft') and resource ('Gmail account'), distinguishing it from sibling tools like 'get_gmail_message_content' or 'search_gmail_messages' that read rather than create content. It further specifies support for 'both new drafts and reply drafts', providing precise scope.
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 that it supports 'new drafts and reply drafts', with examples showing different scenarios. However, it does not explicitly state when to use this tool versus alternatives (e.g., no mention of sibling tools like 'modify_gmail_message_labels' or 'search_gmail_messages'), missing explicit exclusions or comparisons.
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 returns structured results with IDs and web links, supports pagination via page_token, and mentions manual verification capabilities. However, it does not cover aspects like rate limits, authentication requirements, or error handling, leaving some 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 and appropriately sized, with a clear opening sentence followed by bullet-point-like sections for Args and Returns. Every sentence adds value, such as explaining pagination and return format. Minor improvements could include merging some details into a more fluid paragraph, but overall it is efficient and front-loaded.
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 (4 parameters, no annotations, but with an output schema), the description is largely complete. It covers input semantics, behavioral traits like pagination, and output format, though the output schema likely handles return values. It could be more complete by addressing authentication or error scenarios, but it provides sufficient context 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 meaningful semantics for all parameters: 'query' supports Gmail search operators, 'user_google_email' is required, 'page_size' defaults to 10, and 'page_token' is for pagination with usage instructions. This goes beyond the bare schema, though it could provide more detail on query syntax or email format 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 tool's purpose with specific verbs ('searches messages') and resources ('in a user's Gmail account'), distinguishing it from siblings like 'get_gmail_message_content' or 'draft_gmail_message'. It explicitly mentions what it returns (Message IDs, Thread IDs, Gmail web links) and supports (pagination), making the purpose unambiguous.
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 a query, but does not explicitly state when to use this tool versus alternatives like 'search_docs' or 'search_drive_files'. It mentions pagination support, which provides some context, but lacks guidance on prerequisites (e.g., authentication) or exclusions compared to other Gmail-related tools.
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 atomic nature (all-or-nothing execution) and lists operation types, which is helpful. However, it lacks details on permissions needed (e.g., edit access), error handling, rate limits, or what happens on partial failures, leaving behavioral 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. However, the example operations list is detailed, which is useful but slightly reduces conciseness. Overall, most sentences earn their place by clarifying parameters and usage.
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 no annotations and 0% schema coverage, the description does a good job covering parameters and operation types. The output schema exists, so return values need not be explained. However, it could improve by adding more behavioral context like error handling or prerequisites, given the tool's complexity.
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 detailing all three parameters. It explains 'user_google_email' and 'document_id', and provides extensive semantics for 'operations' including operation types, structure, and examples. 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 specific verbs ('executes multiple document operations') and resources ('document'), distinguishing it from siblings like 'modify_doc_text' (single operation) and 'insert_doc_elements' (specific element types). It emphasizes the atomic batch nature, which is a key differentiator.
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 implies usage context by mentioning 'multiple document operations in a single atomic batch update,' suggesting it should be used for bulk edits rather than single changes. However, it does not explicitly state when to use alternatives like 'modify_doc_text' or provide exclusions, leaving some ambiguity for the agent.
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 useful context like the tool's read-only nature (implied by 'retrieves'), parameter interactions (e.g., event_id overriding other parameters), and output formatting details. However, it lacks information on permissions, rate limits, or error handling, 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 a clear purpose statement followed by detailed parameter explanations and return information. It is appropriately sized for a tool with 9 parameters, though some sentences (e.g., in include_attachments) are slightly verbose, slightly reducing efficiency.
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?
The description is largely complete for a retrieval tool with 9 parameters and no annotations, covering purpose, parameters, and returns. However, it lacks details on authentication requirements, error cases, or pagination beyond max_results, which could enhance completeness given the tool's complexity.
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 semantics for all 9 parameters. It explains each parameter's purpose, defaults, interactions (e.g., event_id ignoring other parameters), and usage examples (e.g., RFC3339 format for time_min), adding 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 specific verbs ('retrieves events') and resources ('from a specified Google Calendar'), distinguishing it from siblings like create_event, delete_event, and modify_event by focusing on retrieval rather than creation, deletion, 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 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 this tool (e.g., retrieving single events by ID or multiple events within a time range) and mentions list_calendars for obtaining calendar IDs. However, it does not explicitly state when not to use it or name alternatives for similar retrieval tasks, such as comparing with other sibling tools for event handling.
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 that it returns a formatted list of files/folders with details, mentions default behaviors for parameters, and notes efficiency considerations. However, it lacks information about permissions needed, rate limits, pagination beyond page_size, or whether this is a read-only operation (though implied by 'Searches').
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 a clear opening sentence followed by Args and Returns sections. The content is dense but necessary given the parameter complexity. Some sentences could be slightly more concise (e.g., the corpora explanation is verbose), but overall it's efficiently organized with minimal fluff.
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 (6 parameters, no annotations, 0% schema coverage) and the presence of an output schema (which covers return values), the description does a strong job. It explains all parameters thoroughly and provides behavioral context. However, it could better address authentication needs or error cases to be fully complete for a search tool with many options.
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 semantics for all 6 parameters: explains required vs. optional, default values, behavioral dependencies (e.g., drive_id and corpora interaction), and practical usage notes (e.g., 'Supports Google Drive search operators', efficiency tips). 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 specific action ('Searches for files and folders'), the resource ('within a user's Google Drive, including shared drives'), and distinguishes it from siblings like 'list_drive_items' (which likely lists without search) and 'search_docs' (which searches only Docs files). It provides a complete, unambiguous purpose statement.
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 implies usage for searching Drive files with query capabilities, but does not explicitly state when to use this tool versus alternatives like 'list_drive_items' or 'search_docs'. It provides some contextual guidance (e.g., 'Prefer 'user' or 'drive' over 'allDrives' for efficiency') but lacks explicit when/when-not directives or named 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 of behavioral disclosure. It effectively describes the tool's behavior by explaining how to achieve archiving and deletion through label manipulation, which is crucial context beyond basic parameter documentation. However, it doesn't mention permissions, rate limits, or error handling.
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, usage examples, and parameter documentation. However, the Args and Returns sections are somewhat redundant with the schema and output schema, making it slightly longer than 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 mutation tool with no annotations, the description does a good job explaining key behaviors (archiving/deleting via labels). The output schema exists, so return values don't need explanation. However, it could better address error cases or permissions given the tool's complexity.
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% (only add_label_ids and remove_label_ids have descriptions in the schema). The description adds minimal param semantics in the Args section, mostly restating what's in the schema. It doesn't explain label ID formats or provide examples, so it doesn't fully compensate for the coverage gap.
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 identifies the resource ('a Gmail message'). It distinguishes this tool from siblings like 'manage_gmail_label' (which manages labels themselves) and 'batch_modify_gmail_message_labels' (which handles multiple messages).
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 to use this tool for specific operations: 'To archive an email, remove the INBOX label' and 'To delete an email, add the TRASH label.' This gives clear alternatives to other tools like 'delete_event' or general mutation tools.
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 what the tool does: inspects document structure to find safe insertion points and provides statistics. It outlines a workflow and explains the output format. However, it doesn't mention potential limitations, such as document size constraints or permission requirements, which would be helpful 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 clear sections (e.g., 'USE THIS FOR:', 'CRITICAL FOR TABLE OPERATIONS:', 'WHAT THE OUTPUT SHOWS:', 'WORKFLOW:'), making it easy to scan. However, it includes some redundancy (e.g., repeating insertion index guidance) and could be more concise by integrating the 'Args' and 'Returns' sections more seamlessly. Overall, it's front-loaded with key information but slightly verbose.
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 (inspection with safety implications), no annotations, and an output schema present, the description is highly complete. It explains the purpose, usage guidelines, workflow, and output details thoroughly. The presence of an output schema means the description doesn't need to exhaustively list return values, and it effectively covers the critical aspects needed for safe operation, such as the insertion index logic.
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 lists the three parameters in the 'Args' section but only adds minimal context: 'user_google_email: User's Google email address', 'document_id: ID of the document to inspect', and 'detailed: Whether to return detailed structure information.' This provides basic semantics but lacks details on format (e.g., email validation, document ID sourcing) or the impact of the 'detailed' flag. The description doesn't fully compensate for the schema gap.
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: 'Essential tool for finding safe insertion points and understanding document structure.' It specifies the verb ('finding', 'understanding') and resource ('document structure'), and distinguishes itself from siblings like 'create_table_with_data' by focusing on inspection rather than creation. The title 'inspect_doc_structure' aligns perfectly with this description.
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 to use this tool: 'USE THIS FOR: - Finding the correct index for table insertion - Understanding document layout before making changes - Locating existing tables and their positions - Getting document statistics and complexity info.' It also includes a critical directive: 'ALWAYS call this BEFORE creating tables to get a safe insertion index.' This clearly distinguishes it from alternatives like 'create_table_with_data' or 'insert_doc_elements' by emphasizing its preparatory role.
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 explains the tool's behavior regarding drive scoping and parameter interactions (e.g., 'drive_id' and 'corpora' defaults), but lacks details on permissions needed, rate limits, pagination beyond 'page_size', or error conditions. It adequately describes what the tool does but misses 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.
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 parameter explanations, but it could be more front-loaded. The 'Args' and 'Returns' sections are verbose yet necessary given the complexity. Some redundancy exists (e.g., explaining 'folder_id' defaults twice), but overall it's efficient for a 6-parameter tool.
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 (6 parameters, no annotations, but with an output schema), the description is mostly complete. It covers parameter semantics thoroughly and explains the tool's behavior in different contexts. The output schema handles return values, so the description's brief return statement is sufficient. Minor gaps include lack of error handling or permission details.
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 fully compensate. It provides detailed semantics for all 6 parameters, explaining their purposes, defaults, interactions (e.g., 'drive_id' with 'folder_id'), and conditional behaviors (e.g., 'include_items_from_all_drives' when 'drive_id' is not set). 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 specific verbs ('Lists files and folders') and resources ('supporting shared drives'), distinguishing it from siblings like 'list_docs_in_folder' (specific to Docs) and 'search_drive_files' (search vs. list). It explicitly mentions both personal and shared drive contexts, making the scope unambiguous.
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 to use this tool vs. alternatives: it explains the behavior based on whether 'drive_id' is specified (scoped to shared drive) or not (includes 'My Drive' and accessible shared drives). It also implicitly distinguishes from 'list_docs_in_folder' by handling all file types, not just Docs.
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 and does well by explaining the tool's relationship to the automatic authentication system, clarifying it's for manual initiation only. It doesn't cover rate limits, error responses, or what the OAuth flow actually entails, but provides sufficient context for when to use this versus relying on automatic handling.
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 with a clear purpose statement upfront, followed by important warnings and usage scenarios. Every sentence serves a distinct purpose - establishing the tool's function, warning against misuse, providing specific use cases, and offering the preferred alternative. No wasted words.
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 this is an authentication tool with 2 parameters, 0% schema description coverage, no annotations, but with an output schema, the description provides excellent context about when and why to use this tool. It doesn't explain what the authentication flow returns (covered by output schema) or parameter details, but gives the agent exactly what it needs to decide when to invoke this versus relying on automatic authentication.
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 provides no information about the two parameters (service_name, user_google_email). While the baseline is 3 given the schema handles parameter definitions, the description doesn't compensate for the lack of schema descriptions by explaining what these parameters mean or how they affect authentication.
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 'Manually initiate Google OAuth authentication flow' - a specific verb ('initiate') and resource ('Google OAuth authentication flow'). It clearly distinguishes this authentication tool from all the sibling Google Workspace content manipulation tools listed, making its unique role obvious.
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 exceptional usage guidance with explicit 'when-not' instructions ('should typically NOT be called directly'), clear alternatives ('simply try calling the Google Workspace tool you need'), and three specific scenarios when it should be used (re-authentication, proactive authentication, retry after failure). This gives the agent comprehensive decision-making context.
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 the tool's behavior: it applies formatting to a specified range, accepts color and format inputs, and returns a confirmation string. It also notes default behavior for sheet names. However, it lacks details on permissions, error handling, or rate limits, which would be useful 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 front-loaded: it starts with the core purpose, then details parameter semantics in a clear 'Args' section, and ends with return information. Every sentence adds value, with no redundant or vague language, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 (7 parameters, mutation operation) and lack of annotations, the description is mostly complete: it covers purpose, parameters, and return value. However, it could improve by addressing behavioral aspects like error conditions or permissions. The presence of an output schema (indicating a string return) reduces the need to explain return values in detail.
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 adds significant meaning beyond the schema by explaining each parameter's purpose, format, and examples: user_google_email and spreadsheet_id are required for identification, range_name uses A1-style, colors accept hex strings, and number formats follow Sheets types with examples. This provides clear guidance for parameter usage.
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 ('Applies formatting') and resources ('to a range'), listing the formatting types (background/text color, number/date formats). It distinguishes itself from sibling tools like 'add_conditional_formatting' or 'modify_sheet_values' by focusing on direct range formatting rather than conditional rules or value changes.
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: it specifies that formatting is applied to a range, mentions default behavior (first sheet used if no sheet name provided), and lists the types of formatting supported. However, it does not explicitly state when to use this tool versus alternatives like 'add_conditional_formatting' or 'update_conditional_formatting', nor does it mention any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: it's a retrieval operation (implied read-only), handles batching automatically, has a rate-limiting constraint (25 threads to prevent SSL exhaustion), and mentions the return format. It doesn't cover error handling or authentication details, 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 and front-loaded: the first sentence states the core purpose, the second adds critical constraint, followed by clearly labeled Args and Returns sections. Every sentence earns its place with no wasted words, making it highly scannable and 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 2-parameter tool with no annotations but an output schema, the description is nearly complete. It covers purpose, constraints, parameters, and return format. The output schema exists (indicating structured return data), so the description's brief return statement is sufficient. It could mention authentication requirements more explicitly, but overall provides strong context.
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 thoroughly: 'thread_ids' is described as 'a list of Gmail thread IDs to retrieve' with automatic batching behavior, and 'user_google_email' is explained as 'the user's Google email address' with 'required' designation. This adds complete 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 of multiple Gmail threads'), identifies the resource ('Gmail threads'), and distinguishes it from siblings like 'get_gmail_thread_content' (singular) and 'get_gmail_messages_content_batch' (messages vs threads). The batch nature and thread focus provide precise differentiation.
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 ('in a single batch request') and includes an explicit constraint ('up to 25 threads per batch'). However, it doesn't explicitly mention when NOT to use it or name alternatives like 'get_gmail_thread_content' for single threads, leaving some guidance implicit rather than explicit.
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 what the tool does (shows table structure, dimensions, cell content), how to interpret the output (e.g., 'dimensions: 2x3'), and its role in debugging workflows. However, it lacks details on potential errors, performance characteristics, or authentication needs, though these are somewhat implied by the 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 (e.g., 'USE THIS IMMEDIATELY WHEN:', 'WHAT THIS SHOWS YOU:', 'HOW TO READ THE OUTPUT:'), making it easy to scan. It is appropriately sized for a debugging tool, though some redundancy exists (e.g., repeating parameter info in 'Args' could be streamlined). Every sentence adds value, but minor trimming could improve efficiency.
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 tables), lack of annotations, and 0% schema coverage, the description is highly complete. It covers purpose, usage guidelines, behavioral context, parameter semantics, output interpretation, and integration with workflows. The presence of an output schema (Returns: str with JSON structure) further reduces the need for return value explanations, making this description comprehensive and self-sufficient.
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 schema description coverage is 0%, but the description compensates by explaining all three parameters in the 'Args' section: user_google_email, document_id, and table_index (with clarification that 0 = first table). It adds meaning beyond the bare schema by specifying the table_index default and usage, though it doesn't detail format constraints or examples for the string 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 explicitly states the tool's purpose as an 'ESSENTIAL DEBUGGING TOOL' for when 'tables don't work as expected,' clearly distinguishing it from sibling tools like create_table_with_data or populate_existing_table. It specifies the exact function: to show table structure, dimensions, cell positions, current content, and insertion indices, making the verb+resource combination specific 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 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'), workflow integration steps (e.g., 'After creating table → Use this to verify structure'), and references to sibling tools ('Planning to use populate_existing_table'). It clearly delineates when to use this tool versus alternatives, offering comprehensive guidance.
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 and does an excellent job disclosing behavioral traits. It explains how different file types are handled (Google Docs exported as text, Office files parsed, others downloaded with UTF-8 decode attempt), what happens with binary files, and that it returns plain text with metadata header. This goes well beyond basic parameter documentation.
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: purpose statement first, then bullet points for file type handling, then parameter explanations, then return value. Every sentence earns its place - the bullet points are essential for behavioral transparency, and the Args/Returns sections are necessary given the poor schema coverage. 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 complexity (handling multiple file types with different processing logic), no annotations, 0% schema coverage, but having an output schema, the description is remarkably complete. It covers purpose, behavioral details, parameter semantics, and return format. The output schema handles the return structure, so the description appropriately focuses on the transformation logic and usage context.
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 in the 'Args' section. It clarifies that user_google_email is 'The user's Google email address' and file_id is 'Drive file ID', providing essential semantic context that the bare schema lacks. This is exactly what's needed when schema coverage is minimal.
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 ('Retrieves') and resource ('content of a specific Google Drive file by ID'), including scope ('supporting files in shared drives'). It distinguishes from siblings like get_drive_file_download_url (which returns a URL rather than content) and get_doc_content (which is specific to Docs rather than all Drive files).
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 by specifying it retrieves file content from Google Drive, including shared drives. It doesn't explicitly state when not to use it or name alternatives, but the context is sufficient for an agent to understand this is for extracting readable text from Drive files rather than metadata or URLs.
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 an excellent job disclosing key behavioral traits: it explains the file preparation process, format conversion rules for Google native files, default behaviors, and the critical 1-hour availability window for the download URL. The only minor gap is lack of explicit mention about authentication requirements or rate limits.
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, followed by essential behavioral details, then clear parameter explanations, and finally return value information. Every sentence earns its place with zero wasted text.
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 (format conversions, time-limited URLs) and the presence of an output schema (which handles return value documentation), the description is complete: it covers purpose, behavioral nuances, parameter meanings, and key constraints. No essential information is missing 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.
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 comprehensive parameter semantics: it explains the purpose of 'user_google_email' (required user identification), 'file_id' (target file), and 'export_format' (optional conversion with specific enum values and defaults). The description adds substantial 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 specific action ('Gets a download URL') and resource ('for a Google Drive file'), distinguishing it from sibling tools like 'get_drive_file_content' (which retrieves content directly) or 'get_drive_shareable_link' (which provides a shareable link rather than a time-limited download URL). The purpose is unambiguous and well-differentiated.
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 (to obtain a downloadable URL for Drive files, especially with format conversions for Google native files). It implicitly distinguishes from alternatives by focusing on URL generation rather than direct content retrieval, though it doesn't explicitly name when not to use it or list specific sibling 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 of behavioral disclosure. It effectively describes the batch size limitation (25 messages) and the purpose behind it ('to prevent SSL connection exhaustion'), which are important operational constraints. However, it doesn't mention authentication requirements, rate limits, or error handling for invalid message IDs.
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, operational constraint, and organized parameter/return sections. Every sentence adds value: the first establishes the core function, the second provides critical usage constraint, and the parameter/return sections offer necessary details without redundancy.
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?
For a read operation with 3 parameters and an output schema, the description is complete. It explains the tool's purpose, constraints, all parameters, and return format. The presence of an output schema means the description doesn't need to detail the return structure beyond what's already provided in the 'Returns' section.
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 must compensate. It provides clear explanations for all three parameters: message_ids ('List of Gmail message IDs to retrieve'), user_google_email ('The user's Google email address'), and format ('Message format. "full" includes body, "metadata" only headers'). The format parameter explanation is particularly valuable for understanding the enum options.
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 of multiple Gmail messages'), resource ('Gmail messages'), and scope ('in a single batch request'). It distinguishes from sibling tools like 'get_gmail_message_content' (single message) and 'get_gmail_threads_content_batch' (threads rather than messages).
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 explicitly states when to use this tool ('in a single batch request') and provides clear exclusions/constraints ('Supports up to 25 messages per batch to prevent SSL connection exhaustion'). It implicitly distinguishes from single-message retrieval tools by emphasizing batch capability.
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 the full burden of behavioral disclosure. It thoroughly explains critical behavioral traits: the mandatory workflow with 'inspect_doc_structure', data format requirements (2D list of strings, uniform columns, no None values), index validation needs, and post-creation verification with 'debug_table_structure'. It also mentions the tool's reliability aspect ('one reliable operation') and output details (confirmation with table details and link).
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 well-structured with clear sections (purpose, critical notes, workflow, examples, requirements, args, returns). While comprehensive, some redundancy exists (e.g., repeating 'CRITICAL' points), and the workflow steps could be more condensed. However, every sentence adds value, and it is front-loaded with the core purpose.
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?
For a complex mutation tool with 5 parameters, 0% schema coverage, no annotations, and an output schema, the description is exceptionally complete. It covers the purpose, prerequisites, step-by-step usage, parameter semantics, data formatting rules, index requirements, post-creation verification, and return value explanation. The output schema exists, so the description appropriately focuses on usage rather than return structure.
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 semantics for all parameters. It explains 'user_google_email' and 'document_id' in the context of updating a document, specifies the exact format and constraints for 'table_data' with examples, details how to obtain and validate 'index' from 'inspect_doc_structure', and clarifies the effect of 'bold_headers'. This adds significant 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 'Creates a table and populates it with data in one reliable operation,' which is a specific verb+resource+outcome combination. It clearly distinguishes this from sibling tools like 'create_doc' or 'insert_doc_elements' by focusing on table creation with data insertion, not general document creation or element insertion.
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, step-by-step instructions on when and how to use this tool, including mandatory prerequisites ('ALWAYS call inspect_doc_structure first'), alternatives (using 'debug_table_structure after creation to verify results'), and a clear workflow. It explicitly states critical requirements and exclusions, such as never using arbitrary index values without prior inspection.
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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