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

No annotations are present, so the description must disclose behavior. It merely states the analysis purpose without detailing what 'key features' entails, how the band level is calculated, or what the output structure looks like. This leaves the agent with limited expectations.

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

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

The description is a single sentence that is front-loaded and free of redundancy. It directly communicates the core function with minimal words.

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

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

With an output schema present, return values are documented elsewhere. However, the description lacks contextual information about what analysis is performed and when to use it relative to sibling tools, making it only partially complete for a tool of this complexity.

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

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

The single parameter 'text' is fully described in the schema with a detailed description. The tool description adds only the phrase 'text passage,' which does not exceed the schema's definition. Thus the baseline of 3 applies.

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

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

The description clearly identifies the tool's function as analyzing text for IELTS band level and key features, using a specific verb and resource. This distinguishes it from sibling tools like extract_vocabulary and generate_questions.

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

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

No guidance is provided on when to choose this tool over siblings such as extract_vocabulary or generate_questions. The description only says what it does, not when to use it.

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

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

No annotations are provided, so the description must carry the transparency burden. It discloses that the output includes definitions and examples, which is useful behavioral information. However, it does not mention side effects, limitations (e.g., behavior when text is too long), or how min_band affects output, leaving some gaps.

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

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

The description is a single sentence with no filler words, front-loading the verb and target output. It is appropriately concise, though it could add a bit more context without becoming verbose.

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

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

Given the tool's low complexity, a full input schema, and the presence of an output schema, the description is largely complete. It states the core function and output contents, though it could mention when to use it relative to analyze_text for fuller context.

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

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

The input schema has 100% coverage and fully describes all three parameters (text, count, min_band), including defaults. The description adds no additional meaning to these parameters beyond the schema, so baseline 3 is appropriate.

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

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

The description uses a specific verb ('Extract') and identifies the resource ('IELTS-relevant vocabulary with definitions and examples'), making the purpose clear. It does not explicitly differentiate from sibling tools like analyze_text, but the domain-specific focus on IELTS vocabulary provides reasonable distinction.

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

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

The description implies usage for extracting IELTS vocabulary from provided text, but does not state when to use this tool versus alternatives such as analyze_text, nor does it mention any exclusions or prerequisites. The context is clear enough for a basic use case but lacks explicit guidance.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. However, it only states the function without revealing behaviors like sorting, pagination, default-scope recursion, or authentication requirements. This is a minimal disclosure for a potentially list-heavy operation.

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

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

The description is a single, concise sentence that directly communicates the tool's purpose without unnecessary filler. It earns a top score for efficiency.

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

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

The presence of an output schema and fully documented parameters reduces the need for the description to explain return values or parameter syntax. However, the description lacks context about when this tool is preferred over siblings and gives no behavioral notes, leaving moderate gaps for an AI agent selecting among similar tools.

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

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

The input schema provides complete descriptions for all three parameters (query, folder_id, max_results) with 100% coverage. The description adds no extra meaning beyond the schema, so the baseline score of 3 is appropriate.

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

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

The description clearly states the tool lists files/folders on Google Drive by search keyword, using a specific verb and resource. However, it does not differentiate from sibling tools like gdrive_search, which may also search Google Drive, so it falls short of a 5.

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

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

No guidance is provided about when to use this tool versus alternatives such as gdrive_search or gdrive_list_folder. The description only states what the tool does, leaving the agent to infer the appropriate context.

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

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

No annotations are present, so the description carries the full burden of disclosing behavior. It only states that it lists files, without mentioning whether it includes subfolders recursively, whether folders are included in the output, any permissions needed, or response structure. This is a significant transparency gap for a mutation and listing tool.

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

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

The description is one concise sentence that conveys the core function without any wasted words. It is appropriately sized for a simple, single-purpose tool.

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

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

The tool has one parameter and an output schema exists, so return values do not need explanation. However, the description is minimal and leaves ambiguous whether the listing is recursive or whether subfolders are included, which are important behavioral details for a folder-listing tool. It is minimally viable but not comprehensive.

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

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

The schema covers the only parameter with 100% coverage, and the schema description explains where to obtain the folder_id. The tool description itself adds no parameter-specific details, so the baseline score for high schema coverage is appropriate.

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

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

The description clearly states the tool lists all files inside a specific folder, using a specific verb ('List') and resource ('files inside a folder'). It distinguishes itself from generic listing tools like gdrive_list_files by focusing on a folder scope.

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

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

The description does not explicitly state when to use this tool versus alternatives like gdrive_list_files or gdrive_search. However, the parameter schema for folder_id mentions 'ID của folder (lấy từ gdrive_list_files)', implying that users should first retrieve a folder ID from gdrive_list_files. This offers weak, implied usage context but no direct exclusion or alternative guidance.

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

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

With no annotations, the description carries the burden of behavioral disclosure. It clearly indicates a read operation and enumerates supported formats, implying read-only behavior. However, it does not mention what happens for unsupported file types, error handling, or the exact output structure beyond saying 'text content'.

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

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

The description is extremely concise—two short Vietnamese sentences. The first states the core purpose, and the second lists supported formats. Every word adds value with no filler or redundancy.

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

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

Given the tool's simplicity (one parameter, output schema exists), the description provides essential information: the file_id source and a list of supported formats. It lacks details about handling unsupported formats or errors, but these are not critical for a basic read operation.

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

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

The input schema has 100% coverage for the single parameter file_id, including a description stating where to obtain it. The main description adds no additional parameter semantics beyond what the schema already provides, placing it at the schema-coverage baseline.

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

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

The description uses the specific verb 'Đọc' (read) and clearly identifies the resource as text content of a file from Google Drive. It also lists supported formats (Google Docs, PDF, DOCX, TXT, Sheets, Slides), which distinguishes it from sibling list/search tools.

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

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

The description provides useful context by mentioning that file_id can be obtained from gdrive_list_files or Drive URL, but it does not explicitly compare with sibling tools like read_document or list_documents, nor does it state when to use this tool over alternatives.

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

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

With no annotations provided, the description carries the full burden. It discloses that the search is by name ('theo tên'), which is a key behavioral trait, and implies a read-only operation. However, it does not describe result format, ordering, or whether only IELTS files are returned or if the query filters among all files.

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

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

The description is a single, front-loaded sentence that includes the verb, resource, and scope with no wasted words. It is concise and easy to parse.

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

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

The presence of an output schema and full parameter descriptions covers invocation needs, but the description lacks usage guidance and explicit differentiation from sibling search/list tools. It is adequate for a simple search but not comprehensive in guiding tool selection.

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

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

Schema coverage is 100% with both query and max_results having descriptions. The tool description adds no additional parameter semantics beyond the 'by name' scope, which aligns with the query parameter. Baseline 3 is appropriate since the schema fully documents the parameters.

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

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

The description uses the specific verb 'Tìm kiếm' (search), names the resource 'file IELTS trên Drive' (IELTS files on Drive), and specifies the scope 'theo tên' (by name). This clearly distinguishes it from sibling tools like gdrive_list_files (listing all files) and search_documents (possibly broader search).

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

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

No guidance is provided on when to use this tool versus alternatives such as search_documents or gdrive_list_files. It does not mention exclusions, preconditions, or scenarios where another tool would be more appropriate.

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

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

No annotations are provided, so the description carries the full burden for behavioral disclosure. It only states the core transformation and does not mention potential variability in generated questions, any prerequisites for passage content, or whether the operation has side effects. The generative nature is implied but not elaborated.

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

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

The description is a single, front-loaded sentence that precisely conveys the tool's purpose without redundancy. Every word earns its place.

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

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

For a simple tool with 100% parameter schema coverage and an output schema, the concise description plus schema is sufficient for an agent to invoke it correctly. It lacks usage guidance, but the core functionality is clear.

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

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

Schema description coverage is 100% with each parameter (passage, count, question_type) documented. The tool description adds no extra meaning beyond the schema, but the baseline of 3 applies because the schema sufficiently describes parameters.

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

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

The description uses a specific verb ('Generate') with a clear resource ('a passage') and a specific output type ('IELTS-style practice questions'), distinguishing it from sibling tools like analyze_text or extract_vocabulary. It succinctly states 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.

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

The description implies usage (when a passage needs IELTS practice questions) but provides no explicit context, alternatives, or exclusion criteria. Sibling tools like analyze_text or extract_vocabulary are not referenced, leaving the agent to infer when this tool is preferred.

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

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

With no annotations, the description carries the full transparency burden, but it only restates the tool's basic function. It does not disclose whether the listing is recursive, requires any permissions, or has side effects. Nothing contradicts expectations, but valuable behavioral details are absent.

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

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

The description is a single, clear sentence with no wasted words. It is front-loaded with the verb and resource, making it highly scannable.

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

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

For a simple tool with one optional parameter and an output schema present, the description is mostly sufficient. It clearly names the operation, and the schema covers parameter details. The lack of usage guidance is a minor gap but not critical for this low-complexity tool.

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

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

The input schema already provides 100% coverage for the single optional 'folder' parameter with a clear description (sub-path within documents directory, defaults to root). The tool description adds no parameter information, so the baseline of 3 applies.

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

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

The description clearly states the action ('List') and the resource ('IELTS documents and folders'), making its purpose immediately identifiable. It also distinguishes from siblings like read_document and search_documents by indicating a listing operation over a specific domain.

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

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

No guidance is given about when to use this tool versus alternatives such as search_documents or gdrive_list_folder. The phrase 'IELTS documents' hints at a local repository, but there are no explicit exclusions or context for choosing between similar listing tools.

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

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

With no annotations provided, the description carries the full burden. It discloses that the tool extracts plain text content from selected file formats, which is a behavioral trait, but it does not mention limitations (e.g., scanned PDFs, image-only documents) or how the content is returned. There is no contradiction with annotations since none exist.

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

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

The description is a single sentence that is direct and front-loaded with the action. It includes the essential information about supported formats with no wasted words.

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

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

Given the low complexity (one well-documented parameter) and the presence of an output schema, the description is mostly complete. It covers the supported document types, which is the main contextual need, though it could briefly mention behavior for unsupported or missing files. Overall, it is sufficient without needing to explain return values due to the output schema.

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

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

The schema provides 100% coverage for the single 'path' parameter with a detailed description and example. The tool description does not add meaning beyond the schema, so the baseline 3 applies.

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

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

The description clearly states the verb 'read', the resource 'document', and explicitly lists supported file types (PDF, DOCX, TXT). This distinguishes it from sibling tools like gdrive_read_file, which reads from Google Drive, and list_documents, which lists documents rather than reading content.

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

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

The description implies usage for reading local documents but does not explicitly state when to use this tool over alternatives like gdrive_read_file or search_documents. There are no exclusions or alternative recommendations, leaving the context implied rather than explicit.

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

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

With no annotations, the description carries the full burden. It only says 'search by filename' and does not disclose behavioral traits like case-insensitivity, result limits, or the source of documents. The schema covers some parameter details, but the tool's overall behavior is largely opaque.

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

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

The description is a single, front-loaded sentence with no filler. It communicates the core purpose efficiently and earns no redundancy.

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

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

The output schema exists and parameters are well-documented, but the description lacks usage context and fails to clarify how this tool differs from similar siblings. It is minimally adequate for a simple search tool, but not comprehensive.

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

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

Schema description coverage is 100%, so the schema already explains both 'query' and 'max_results'. The description adds no additional parameter semantics, but the baseline of 3 is appropriate since the schema handles the burden.

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

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

The description states a clear verb ('Search'), resource ('documents'), and scope ('by filename'). It is specific enough to differentiate from listing tools like list_documents, though it does not explicitly distinguish from gdrive_search, preventing a perfect score.

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

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 siblings like list_documents or gdrive_search. There are no exclusions, prerequisites, or alternative recommendations.

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