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 only states the action ('Ask a question') without any details on traits like response format, rate limits, authentication needs, or potential side effects. This is inadequate for a tool with no annotations, as it leaves key 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.

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

The description is extremely concise with a single sentence ('Ask a question to the LLM'), which is front-loaded and wastes no words. It efficiently conveys the core action without unnecessary elaboration, making it easy to parse quickly.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns, how responses are formatted, or any behavioral nuances. For a tool with no structured data to supplement it, the description should provide more context 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?

The schema description coverage is 100%, with clear descriptions for both parameters ('question' and 'context'). The description adds no additional meaning beyond the schema, such as examples or constraints. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, but no extra value is provided.

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 'Ask a question to the LLM' states a clear verb ('Ask') and resource ('question'), but it's vague about what the LLM is and lacks specificity. It doesn't distinguish this tool from its siblings (e.g., generate_code, generate_code_to_file, generate_documentation), which also involve LLM interactions but for different purposes. The purpose is understandable but minimal.

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 its siblings. It doesn't mention alternatives, exclusions, or context for usage. For example, it doesn't clarify if this is for general queries versus code generation or documentation tasks, leaving the agent with no explicit usage instructions.

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 only states the basic action ('generate code') without mentioning permissions, rate limits, response format, or any constraints. This is inadequate for a tool with potential complexity in code generation.

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 with a single sentence ('Generate code based on a description'), which is front-loaded and wastes no words. However, this conciseness comes at the cost of completeness, as noted in other dimensions.

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 of code generation, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits, usage context, and output expectations, making it insufficient for an AI agent to understand the tool fully.

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. The description adds no meaning beyond what the schema provides, as it doesn't explain parameter interactions or usage examples. Baseline 3 is appropriate since the 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 states what the tool does ('Generate code based on a description'), which is clear but vague. It specifies the verb 'generate' and resource 'code', but doesn't distinguish it from sibling tools like 'generate_code_to_file' or 'generate_documentation', leaving ambiguity about scope and output format.

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. There are sibling tools like 'generate_code_to_file' and 'generate_documentation', but no explicit or implied context for choosing between them, such as output destination or purpose.

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 offers minimal behavioral disclosure. It mentions writing to files and line-based insertion/replacement, but doesn't address critical behaviors like: whether existing file content is preserved/modified, error handling for invalid paths/line numbers, authentication requirements, or rate limits. For a file-writing 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 sentence that front-loads the core functionality. Every word earns its place: 'Generate code' (action), 'write it directly to a file' (destination), 'at a specific line number' (precision). No redundant or vague phrasing.

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 complex file-writing tool with 6 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what happens on success/failure, how insertion vs replacement works, file encoding considerations, or interaction with existing content. The agent lacks sufficient context to use this tool safely and 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?

Schema description coverage is 100%, so parameters are well-documented in the schema. The description adds minimal value beyond schema: it mentions 'specific line number' (implied by lineNumber parameter) and 'write it directly to a file' (implied by filePath). No additional syntax, format, or usage details are provided beyond what the schema already describes.

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 ('Generate code and write it directly to a file') with precise resource targeting ('at a specific line number'). It distinguishes from sibling tools like 'generate_code' (which likely doesn't write to files) and 'generate_documentation' (different output type). The verb+resource combination is 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 no guidance on when to use this tool versus alternatives. It doesn't mention when to choose this over 'generate_code' (which might return code without writing to file) or 'ask_question' (for clarification). There are no prerequisites, exclusions, or comparative context provided.

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 for behavioral disclosure. 'Generate documentation for code' implies a creation/write operation but doesn't specify whether this is a read-only analysis, whether it modifies existing files, what permissions are needed, or what the output looks like. It lacks details about rate limits, error conditions, or whether the tool actually creates files or returns documentation text.

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 at just four words: 'Generate documentation for code.' It's front-loaded with the core action and resource, with zero wasted words. Every word earns its place by communicating the essential purpose without 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?

Given the complexity of a documentation generation tool with 3 parameters and no annotations or output schema, the description is insufficient. It doesn't explain what kind of documentation is generated, whether it includes examples or explanations, what the return format is, or any limitations. For a tool that presumably produces structured output, more context is needed beyond the minimal purpose statement.

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 (code, language, format) with clear descriptions. The tool description adds no additional parameter information beyond what's in the schema. According to scoring rules, when schema 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 tool's purpose with a specific verb ('Generate') and resource ('documentation for code'). It distinguishes from sibling tools like 'generate_code' and 'ask_question' by focusing on documentation generation rather than code creation or question answering. However, it doesn't explicitly differentiate from all siblings (e.g., 'generate_code_to_file' might share some conceptual overlap).

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 documentation generation is appropriate, what types of code benefit most, or how it differs from manual documentation. With siblings like 'generate_code' and 'ask_question', there's no indication of when to choose documentation generation over those options.

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