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 explains what the tool counts (translatable cells) and excludes (formulas, numbers, dates, empty cells). It gives important file-handling instructions, including not showing base64 content to the user and using resource URI for uploaded files. This provides good transparency, though it could mention error cases or performance.

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

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

The description is front-loaded with the core purpose, followed by usage instructions. It is fairly concise given the need to clarify file-handling nuances, but could be slightly tighter. The structure is logical: purpose, what it counts, usage instructions, important note.

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 counting tool with 3 optional parameters and no output schema, the description adequately covers what the tool does, how to use it, and key behavioral notes. It does not explain error handling or return format, but the return value (count) is simple. Overall, it is complete enough for effective use.

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%, so the schema already describes parameters. The description adds value by explaining the usage scenarios for each parameter (local files, uploaded files, base64) and providing the critical 'provide either/or' instruction. This goes beyond the schema descriptions, aiding correct tool invocation.

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: counting translatable cells in an Excel file. It specifies what is counted (text) and excluded (formulas, numbers, dates, empty cells). This distinguishes it from sibling tools like translate_excel (which performs translation) or estimate_translation_cost (which likely estimates cost), making its function unambiguous.

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 explicit instructions on when to use each parameter (local file, uploaded file, base64) and states that either file_path or file_content_base64 should be provided, not both. It also notes the tool is useful for estimating translation scope and cost. However, it does not explicitly compare to sibling tools or state when not to use it, which would earn a 5.

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?

Even without annotations, the description fully discloses behavior: it returns estimates (not actual translations), explains constraints on input, and includes privacy guidance (not showing base64). No side effects or destructive actions are implied, which is appropriate for a read-only estimation 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?

Description is front-loaded with purpose and returns, then organized with numbered usage instructions and an important note. Every sentence adds value without redundancy. Despite moderate length, information density is high.

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 no output schema or annotations, the description covers all essential aspects: what the tool does, what inputs are needed, how to use each input modality, and what output to expect. It provides complete guidance for an AI agent to select and invoke the tool 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?

All three parameters are described in the schema (100% coverage) and the description adds meaningful context: 'file_path' for local files, 'file_content_base64' for base64 input, 'sheets' for filtering. It also clarifies mutual exclusivity of the file 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 clearly states the tool estimates translation cost for an Excel file and lists specific return values (cell count, API cost, processing time). It is distinct from sibling tools like 'translate_excel' (which performs translation) and 'count_translatable_cells' (which counts cells without cost estimation).

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?

Provides explicit instructions for different input types (local file path, uploaded file, base64), warns against providing both file_path and file_content_base64, and advises not to show base64 content to the user. This gives clear when-to-use guidance and prevents misuse.

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 responsibility. It discloses the mutual exclusivity of file_path and file_content_base64, and instructs the agent on how to handle each case. It does not cover error behaviors or file format limitations, but the core usage constraints are well communicated.

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

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

The description is well-structured with clear headings (USAGE INSTRUCTIONS, IMPORTANT) and front-loaded with the purpose. While it is longer than necessary, each sentence adds meaningful guidance. A minor redundancy exists in the important note, but overall it is efficient.

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

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

The description states the tool returns a list of sheet names, which matches its name. However, it does not detail the return format or mention what happens in error cases (e.g., invalid file). Given that no output schema exists, more detail on the output would improve 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?

The input schema already describes both parameters with 100% coverage. The description adds value by providing concrete examples and step-by-step usage instructions for each parameter, as well as the important mutual exclusivity rule, which goes beyond the schema definitions.

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 starts with 'Get the list of sheet names in an Excel file,' which is a clear verb and resource. It also explains the tool's usefulness in the context of translation, distinguishing it from sibling tools like translate_excel that perform actual modifications.

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 detailed usage instructions for different scenarios (local files, uploaded files, base64 input) and includes a clear note to not show base64 content to the user. However, it does not explicitly compare this tool to its siblings, so the guidance on when to use alternatives is implied rather than 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?

No annotations are provided, so the description is the sole source of behavioral info. It states the tool is non-destructive and previews cells, but does not detail whether it requires file access or any side effects. Important behavioral notes like file_path vs base64 exclusivity are included, but overall transparency is moderate.

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

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

The description is well-structured with a summary, numbered usage instructions, and an important note. It is concise but includes necessary details. Each sentence adds value, though a minor redundancy exists.

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 no output schema or annotations, the description covers the tool's purpose, input methods, and key usage notes. It provides sufficient context for an agent to decide when to use it. The output format is not described, but for a preview tool this is acceptable.

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 a baseline of 3. The description adds significant meaning: it explains the purpose of each parameter (e.g., file_path for local files) and provides important usage context (e.g., default limit, mutually exclusive parameters). This goes beyond the schema's descriptions.

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: preview translatable cells from an Excel file. It explains what it returns (first N cells with location and content) and when to use it (before full translation), distinguishing it from sibling tools like translate_excel.

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 explicit usage instructions for different input types (local files, uploaded files, base64). It explains that the tool is useful for understanding what will be translated, giving clear context. However, it lacks explicit exclusions of when not 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 carries the full burden. It states that the tool preserves formatting, formulas, images, and charts, and that the response contains base64-encoded data. This provides useful behavioral context beyond the schema.

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 excessively long and includes imperative instructions for the AI agent (e.g., 'DO THIS AUTOMATICALLY', 'DO NOT ask for permission'). These are not typical tool usage instructions and add verbosity. The core purpose is buried in procedural details.

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 complexity (7 parameters, no output schema), the description covers file handling, languages, and expected output. It explains how to provide the file and what the response looks like. However, it lacks error scenarios or behavior when conflicts arise (e.g., both file_path and file_content_base64 provided).

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%, so baseline is 3. The description adds context for the 'file_content_base64' and 'file_path' parameters, explaining when to use each. It also clarifies the 'context' parameter and provides a workflow. This adds value beyond the schema.

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 translates Excel files and preserves formatting, formulas, images, and charts. It distinguishes from siblings like translate_texts by focusing on Excel. However, the inclusion of automatic behavior instructions slightly blurs the core purpose.

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 explicitly specifies when to use the tool: when a user uploads a file and asks to translate. It provides a step-by-step process. It does not mention when not to use it or alternative tools, but sibling tools are listed for 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?

With no annotations provided, the description covers automatic behavior, language support, and source language auto-detection. It does not disclose potential limitations like rate limits, max text length, or cost, which would improve transparency. No contradictions with annotations (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 front-loaded with clear purpose but includes a verbose 'AUTOMATIC BEHAVIOR' section that could be more concise. While informative, it contains redundant instructions (e.g., repeat of example) that could be streamlined.

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 description lacks details on the output format (e.g., array of translated texts, order, metadata), error handling, or limits. Given no output schema, this is a significant gap. It partially compensates with an example but falls short of 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 coverage is 100%, so baseline is 3. The description adds value by listing all supported languages (beyond the schema's examples) and showing parameter usage in a concrete example, enhancing understanding beyond the schema alone.

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 translates text strings to a target language using AI. It specifies the verb 'translate' and resource 'text strings', and distinguishes from siblings like translate_excel which handles file-level operations. The example further clarifies the 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 provides explicit instructions on when to use the tool automatically without asking, including a worked example. However, it does not mention alternative tools like translate_excel or conditions where this tool should not be used, leaving some ambiguity.

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