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 ('adds a formula') but doesn't cover critical aspects like whether this overwrites existing cell content, requires file permissions, has side effects, or returns any confirmation. For a mutation tool with zero annotation coverage, this is a significant gap.

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

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

The description is a single, efficient sentence in Japanese that directly states the tool's function. It's front-loaded with the core action and has no wasted words, making it highly concise and well-structured for quick comprehension.

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

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

Given the tool's complexity (a mutation operation with 4 required parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't address behavioral traits, usage context, or what happens post-execution (e.g., success confirmation or error handling), leaving the agent under-informed.

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

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

The description adds no parameter semantics beyond what the input schema provides. Since schema description coverage is 100% (each parameter has a clear description in Japanese), the baseline is 3. The tool description doesn't compensate with additional context like formula syntax examples or file path requirements.

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 'セルに数式を追加します' (Adds a formula to a cell) clearly states the verb ('adds') and resource ('formula to a cell'), making the tool's purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'set_cell_value' or 'set_range_values', which might also modify cell content, so it's not a perfect 5.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., file must exist), exclusions, or compare it to siblings like 'set_cell_value' for non-formula content. This leaves the agent guessing about appropriate contexts.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a write operation ('adds') but doesn't mention permission requirements, whether the operation is reversible, what happens if a sheet with the same name exists, or any rate limits. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps.

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

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

The description is a single, efficient sentence in Japanese that directly states the tool's purpose. It's appropriately sized for a simple tool, though it could be slightly more front-loaded with key constraints. No wasted words or unnecessary elaboration.

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

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

For a mutation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what the tool returns, error conditions, or important behavioral aspects like what happens when adding duplicate sheet names. The description should provide more context given the tool's complexity as a write 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?

Schema description coverage is 100%, so the schema already fully documents both parameters with good descriptions. The tool description adds no additional parameter information beyond what's in the schema. According to scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description.

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 ('adds a worksheet') and target resource ('to an existing workbook'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'create_workbook' (which creates new workbooks) or 'get_workbook_info' (which reads workbook information), though the distinction is somewhat implied by the 'existing workbook' context.

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 minimal guidance - it mentions 'existing workbook' which implies when to use this vs. 'create_workbook', but doesn't offer explicit when/when-not instructions or mention alternatives like modifying existing worksheets. No prerequisites or constraints beyond the 'existing workbook' requirement are stated.

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

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

With no annotations provided, the description carries full burden and does well by disclosing critical behavioral traits: the workbook is created empty without sheets, and users must use add_worksheet tool before data manipulation. This provides important context about the tool's limitations and required follow-up actions.

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 perfectly concise with two sentences that each earn their place: the first states the core purpose, the second provides crucial behavioral context. No wasted words, front-loaded with the main action.

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 creation tool with no annotations and no output schema, the description does well by explaining the workbook's empty state and required next steps. However, it doesn't mention what happens if the file already exists at the path, or what the tool returns (success/failure indication), leaving some gaps in completeness.

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 fully documents the single filePath parameter. The description doesn't add any parameter-specific information beyond what's in the schema, maintaining the baseline score of 3 when schema does the heavy lifting.

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 specific action ('新しいExcelワークブックを作成します' - creates a new Excel workbook) and resource (Excel workbook), distinguishing it from siblings like add_worksheet or get_workbook_info by focusing on creation rather than modification or retrieval.

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 clear context about when to use this tool (to create a new Excel workbook) and includes important behavioral notes about the workbook being empty without sheets, but doesn't explicitly state when NOT to use it or name specific alternatives among the sibling tools.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the export action but doesn't describe traits like whether it overwrites existing CSV files, requires specific file permissions, handles errors, or returns any output (e.g., success confirmation or file path). This leaves significant gaps for a mutation tool that creates 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, efficient sentence in Japanese that directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy to understand at a glance.

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

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

Given the tool has 3 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain behavioral aspects like file handling, error cases, or what happens post-export (e.g., if it returns a confirmation). For a tool that performs file operations, this lack of context is a significant gap.

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

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

The schema description coverage is 100%, with clear parameter descriptions in Japanese (e.g., 'CSVファイルの出力パス' for csvPath). The description adds no additional parameter meaning beyond the schema, so it meets the baseline of 3 where the schema does the heavy lifting without compensating for gaps.

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

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

The description clearly states the action ('エクスポートします' - exports) and resource ('ワークシートをCSVファイルに' - worksheet to CSV file), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'get_range_values' or 'get_workbook_info' that might also retrieve data, though those don't explicitly export to CSV.

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. It doesn't mention prerequisites (e.g., needing an existing Excel file), exclusions, or compare to siblings like 'get_range_values' for data retrieval without export. The description is standalone with no contextual usage hints.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool searches for values but doesn't describe what happens when multiple matches are found, whether the search is case-sensitive, if it returns cell locations or just values, or any error conditions. For a search operation with zero annotation coverage, this leaves significant behavioral questions unanswered.

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

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

The description is extremely concise - a single Japanese sentence that directly states the tool's function. There's no wasted language or unnecessary elaboration. While it could benefit from more detail, what's present is perfectly efficient and front-loaded with the core purpose.

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

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

Given that this is a search tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what the tool returns (locations, values, both?), how results are formatted, whether there are limitations on search scope, or what happens with no matches. For a tool that presumably returns search results, the lack of output information is a significant gap.

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 documents all three parameters thoroughly. The description doesn't add any additional meaning beyond what's in the schema - it mentions searching for specified values in a worksheet, which aligns with but doesn't expand upon the parameter descriptions. With complete schema coverage, 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 states the tool's purpose as searching for specified values within a worksheet, which is clear but generic. It doesn't distinguish this from similar sibling tools like 'get_cell_value' or 'get_range_values' that also retrieve data from worksheets. The description is accurate but lacks specificity about what makes this tool unique.

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

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

No guidance is provided on when to use this tool versus alternatives. With sibling tools like 'get_cell_value' (for single cells) and 'get_range_values' (for ranges), the description doesn't explain that this tool searches across the entire worksheet or how it differs from those options. There's no mention of prerequisites, limitations, or typical use cases.

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

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 '設定します' implies a write/mutation operation, the description doesn't clarify whether this overwrites existing formatting, requires file write permissions, has side effects on other cells, or provides any confirmation/error response. For a mutation tool with complex nested parameters, this leaves significant behavioral gaps.

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

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

The description is a single, efficient Japanese sentence that directly states the tool's purpose with zero wasted words. It's appropriately sized for a formatting tool and front-loads the essential information (what formatting aspects are supported). 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 mutation tool with complex nested parameters (4 params with deep nesting) and no annotations or output schema, the description is insufficient. It doesn't address behavioral aspects like error conditions, permission requirements, or what happens on success/failure. The agent must rely entirely on the input schema for operational details, which is risky for a write 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?

Schema description coverage is 100%, so the schema already documents all 4 parameters thoroughly. The description mentions the three formatting aspects (font, fill, border) which map to the 'format' parameter's structure, but adds no additional semantic context beyond what's in the schema descriptions. This meets the baseline for high schema coverage.

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 ('設定します' - sets/configure) and the resource ('セルの書式' - cell formatting), specifying the three formatting aspects (font, fill, border). It distinguishes this tool from sibling tools like 'set_cell_value' or 'set_range_values' which handle content rather than formatting. However, it doesn't explicitly differentiate from potential formatting alternatives that might exist.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (like needing an existing workbook), compare with sibling tools like 'set_range_values' for bulk formatting, or indicate when formatting vs content-setting tools are appropriate. The agent must infer usage from the tool name and parameters alone.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves a cell value, implying a read-only operation, but doesn't cover critical aspects like error handling (e.g., what happens if the file doesn't exist), performance (e.g., speed or limitations), or output format (e.g., data type returned). For a tool with no annotation coverage, 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.

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

The description is extremely concise and front-loaded: a single sentence that directly states the tool's purpose. There is zero waste or redundancy, making it easy to parse quickly. This efficiency is ideal for a simple tool, though it may lack depth for more complex scenarios.

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

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

Given the tool's complexity (3 required parameters, no output schema, and no annotations), the description is incomplete. It doesn't explain the return value (e.g., what data type is returned, such as string or number), error conditions, or how it interacts with sibling tools. For a read operation in a spreadsheet context, more detail on behavior and output would be necessary for an agent to use it effectively.

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

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

The description adds no parameter semantics beyond what the input schema provides. The schema has 100% description coverage, with clear explanations for 'cell' (cell position in A1 format), 'filePath' (absolute path to Excel file), and 'sheetName' (worksheet name). Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't compensate with additional context like examples or constraints.

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

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

The description clearly states the tool's purpose: '指定されたセルの値を取得します' (Get the value of the specified cell). It uses a specific verb ('取得します' - get/retrieve) and resource ('セルの値' - cell value), making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'get_range_values' or 'set_cell_value', which would require more specific language about scope or operation type.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_range_values' (for multiple cells) or 'set_cell_value' (for writing), nor does it specify prerequisites such as needing an existing Excel file. Without this context, an agent might struggle to choose between similar 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, the description carries full burden but only states it retrieves data. It doesn't disclose behavioral traits such as read-only nature (implied but not stated), error handling, performance, or output format. For a tool with 3 parameters and no annotations, this is a significant gap.

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

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

The description is a single, efficient sentence in Japanese with no wasted words. It's appropriately sized and front-loaded, though it could be more informative. Every sentence earns its place, but it's under-specified rather than concise.

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 3 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain the Excel context, return values, or error conditions. For a data retrieval tool in a sibling-rich environment, more context is needed to be fully helpful.

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 fully documents parameters (filePath, range, sheetName). The description adds no meaning beyond what the schema provides, as it doesn't explain parameter interactions or usage examples. Baseline 3 is appropriate when schema does the heavy lifting.

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 '指定された範囲のデータを取得します' (Retrieves data from a specified range) states the basic purpose with a verb (取得/retrieves) and resource (データ/data), but it's vague about the context (Excel files) and doesn't distinguish from siblings like get_cell_value or find_data. It's adequate but lacks specificity.

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. The description doesn't mention Excel context, prerequisites, or compare to siblings like get_cell_value (single cell) or find_data (search-based). Usage is implied but not 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?

No annotations are provided, so the description carries full burden. It states this is a read operation ('取得します'), but doesn't disclose important behavioral traits: whether it requires specific file permissions, what happens with invalid file paths, if it works with password-protected files, what metadata fields are returned, or any rate limits. For a file access tool with zero annotation coverage, this leaves significant gaps.

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

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

The description is a single, efficient Japanese sentence that directly states the purpose with examples. It's appropriately sized for a simple tool, though it could be slightly more structured by separating purpose from examples. No wasted words 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 this is a file access tool with no annotations and no output schema, the description is incomplete. It doesn't explain what '詳細情報' (detailed information) includes beyond the examples, nor the return format. For a tool that presumably returns structured workbook metadata, more context about output expectations would help the agent use it correctly.

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 the single parameter 'filePath' well-described in the schema as '情報を取得するExcelファイルの絶対パス' (absolute path of Excel file to get information from). The description adds no additional parameter context beyond what the schema provides, so it meets the baseline for high schema coverage without compensating value.

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 ('取得します' - get/retrieve) and resource ('Excelワークブックの詳細情報' - Excel workbook detailed information), with specific examples of what information is included ('シート一覧、メタデータ等' - sheet list, metadata, etc.). It distinguishes from siblings like get_cell_value or get_range_values by focusing on workbook-level metadata rather than cell/range data. However, it doesn't explicitly differentiate from other potential metadata tools (none exist in siblings).

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when this tool is appropriate versus get_cell_value or get_range_values for different information needs, nor does it specify prerequisites like file accessibility or format requirements. 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.

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 sets a value but doesn't mention whether this is a write operation, if it overwrites existing data, what permissions are needed, or error handling. This is inadequate for a mutation tool with zero annotation coverage.

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

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

The description is a single, efficient sentence in Japanese that directly states the tool's purpose without any fluff. It's appropriately sized and front-loaded, with every word earning 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?

Given this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects like side effects, error cases, or return values, leaving significant gaps for the agent to understand the tool's full 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 schema description coverage is 100%, so the schema already documents all four parameters thoroughly. The description adds no additional meaning beyond what the schema provides, such as examples or constraints, meeting the baseline for high schema coverage.

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 ('set a value') and the target ('specified cell'), which is a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'set_range_values' or 'format_cell', which would require a 5.

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

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 'set_range_values' for multiple cells or 'add_formula' for formulas. It lacks context about prerequisites or exclusions, leaving the agent to infer usage from the schema alone.

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

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

With no annotations provided, the description carries full burden but only states what the tool does, not behavioral traits. It doesn't disclose whether this overwrites existing data, requires file permissions, has file size limits, or what happens on success/failure. For a write operation 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.

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

Single sentence, zero waste. Every word contributes to the core purpose. The description is appropriately sized and front-loaded with the essential action.

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 write operation with 4 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what happens to existing data in the range, error conditions, or return values. The schema covers parameter documentation well, but behavioral context is missing.

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%, providing good documentation for all 4 parameters. The description adds minimal value beyond the schema - it mentions '2次元配列のデータ' which aligns with the values parameter schema, but doesn't provide additional context about parameter interactions or edge cases.

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 ('設定します' - sets) and resource ('2次元配列のデータ' - 2D array data) with the target ('指定された範囲' - specified range). It distinguishes from siblings like set_cell_value (single cell) and get_range_values (read operation), but doesn't explicitly mention Excel/worksheet context which is only in the schema.

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 on when to use this tool versus alternatives like set_cell_value (for single cells) or add_worksheet (for creating sheets). The description implies it's for writing 2D arrays to ranges, but doesn't provide explicit comparison or exclusion criteria.

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