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 that the configuration is read from environment variables, which is useful context. However, it doesn't describe the return format, potential errors (e.g., if environment variables are missing), or any side effects. For a read operation with zero annotation coverage, this is insufficient, 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 concise and front-loaded: the first sentence clearly states the purpose, and the second briefly notes the return. There's no wasted text, and it's appropriately sized for a simple tool. However, the structure could be slightly improved by integrating the return note more seamlessly, but it's still 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?

Given the tool's simplicity (0 parameters, output schema exists), the description is somewhat complete but has gaps. It explains what the tool does and the data source (environment variables), but lacks usage guidelines and behavioral details like error handling. The presence of an output schema means it doesn't need to explain return values, but other contextual elements are missing, making it adequate but not 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 tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to add parameter semantics, so a baseline of 4 is appropriate. It implicitly confirms there are no required inputs by not mentioning any, which aligns with 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's purpose: '获取当前使用的SMTP配置（从环境变量读取）' (Get the currently used SMTP configuration, read from environment variables). It specifies both the verb ('获取' - get) and resource ('SMTP配置' - SMTP configuration), and distinguishes itself from siblings like 'get_smtp_configs' by focusing on the 'current' configuration from environment variables. However, it doesn't explicitly contrast with all siblings, keeping it at 4 rather than 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 when to use it over 'get_smtp_configs' (which might retrieve multiple or all configurations) or in relation to the email-sending siblings. There's no context about prerequisites, such as needing environment variables set, or exclusions. This lack of usage guidance is a clear gap.

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 returns SMTP configuration information in JSON format, which is useful. However, it doesn't disclose critical behavioral traits such as whether this is a read-only operation (implied but not stated), potential rate limits, authentication requirements, or what specific 'common email services' are included. The description adds some value but leaves significant gaps for a tool with no 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 concise and front-loaded: the first sentence states the purpose clearly, and the second specifies the return format. There's no wasted text, and both sentences earn their place by providing essential information. However, it could be slightly more structured (e.g., separating purpose and returns more distinctly), but it's efficient overall.

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 (0 parameters, no annotations, but has an output schema), the description is minimally adequate. It states what the tool does and the return format, which is helpful since an output schema exists (so return values needn't be explained). However, it lacks context on usage, behavioral details, and sibling differentiation, making it incomplete for optimal agent guidance. It meets the minimum viable threshold but has clear gaps.

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 tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to add parameter semantics since there are none. It appropriately doesn't discuss parameters, so it meets the baseline for a zero-parameter tool. No additional compensation is needed.

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: '获取常用邮箱的SMTP配置信息' (Get SMTP configuration information for common email services). It specifies both the verb (get) and resource (SMTP configurations), though it doesn't explicitly differentiate from sibling tools like 'get_current_config' which might retrieve different configuration types. The purpose is clear but lacks sibling differentiation.

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 'send_email' and 'send_email_with_custom_config' that might relate to SMTP usage, but the description doesn't mention when this configuration retrieval is needed (e.g., before sending emails, for setup purposes) or when to choose other tools. No explicit or implied usage context is 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool sends emails but doesn't mention authentication requirements, rate limits, error conditions, whether it's synchronous/asynchronous, or what constitutes '发送结果信息' (sending result information). 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 efficiently structured with a purpose statement followed by categorized parameter documentation. Every sentence serves a purpose. The bilingual nature (Chinese purpose, English parameter names) is slightly inconsistent but doesn't significantly impact utility.

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 7-parameter mutation tool with no annotations, the description covers basic functionality and parameters adequately. However, it lacks behavioral context (auth, errors, limits) and doesn't leverage the output schema to explain return values. Given the complexity and zero annotation coverage, it should provide more operational guidance.

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

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

With 0% schema description coverage, the description compensates well by documenting all 7 parameters in Chinese with clear explanations. It specifies which are optional, provides content_type enum values ('plain' vs 'html'), and clarifies parameter purposes. However, it doesn't explain format details like attachment path requirements or email address validation.

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: '发送完整邮件（支持多个收件人、附件、CC、BCC）' which translates to 'Send complete email (supports multiple recipients, attachments, CC, BCC)'. This specifies the verb ('send') and resource ('complete email') with feature highlights. However, it doesn't explicitly differentiate from sibling tools like 'send_simple_email' or 'send_email_with_custom_config'.

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 ('send_simple_email', 'send_email_with_custom_config'). There's no mention of prerequisites, alternative scenarios, or comparative context. The agent must infer usage from the tool name and parameter list 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 for behavioral disclosure. While it mentions the action (sending email) and lists parameters, it doesn't describe important behavioral aspects like error handling, rate limits, authentication requirements beyond password, what happens with attachments, or whether this is a synchronous/blocking operation. The description is functional but lacks critical operational context.

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

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

The description is well-structured with clear sections (Args, Returns) and uses bullet-like formatting, but it's quite lengthy due to documenting 13 parameters. While each parameter explanation earns its place given the 0% schema coverage, the overall description could be more front-loaded with critical usage information before the detailed parameter list.

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 13-parameter tool with no annotations and 0% schema coverage, the description does an adequate job documenting parameters but lacks important contextual information. While it has an output schema (mentioned in Returns), the description doesn't provide behavioral context about authentication, error conditions, or how this tool differs from its siblings. The parameter documentation is strong, but overall completeness is limited by missing operational guidance.

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?

With 0% schema description coverage, the description provides comprehensive parameter documentation that fully compensates. Each parameter is clearly explained with examples (e.g., 'smtp.qq.com, smtp.gmail.com'), port guidance ('25/465/587'), content type options ('plain' or 'html'), and practical advice about TLS/SSL usage with specific ports. Optional parameters are clearly marked, and the parameter explanations add significant value beyond what the bare schema provides.

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 ('使用自定义SMTP配置发送邮件' - send email with custom SMTP configuration), which distinguishes it from sibling tools like 'send_email' and 'send_simple_email' that presumably use default configurations. The verb+resource combination is precise and 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 the sibling tools like 'send_email' or 'send_simple_email'. It doesn't mention prerequisites, alternative scenarios, or any context that would help an agent choose between this and other email-sending tools on the server.

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 sends emails but does not mention any behavioral traits such as authentication requirements, rate limits, error handling, or whether it's a synchronous operation. The description lacks critical details needed for safe and effective use, especially for a mutation tool with potential side effects.

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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by a structured 'Args' and 'Returns' section. Every sentence earns its place by providing essential information without redundancy, making it easy to scan and understand 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 tool's complexity (a mutation tool with 4 parameters), no annotations, and an output schema present (implied by 'Returns: 发送结果信息'), the description is moderately complete. It covers the purpose and parameters well but lacks behavioral context like permissions or error handling. The output schema likely details return values, so the description doesn't need to explain those, but overall gaps remain for safe usage.

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 0%, so the description must compensate. It adds significant meaning beyond the schema by explaining each parameter's purpose in Chinese: 'receiver_email' as '收件人邮箱地址' (recipient email address), 'subject' as '邮件主题' (email subject), 'content' as '邮件内容（纯文本或HTML）' (email content, plain text or HTML), and 'content_type' with enum values 'plain' and 'html'. This clarifies semantics effectively, though it doesn't cover format details like email validation or content length limits.

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: '发送简单邮件（单个收件人，无附件）' which translates to 'Send simple email (single recipient, no attachments)'. This specifies the verb ('send'), resource ('email'), and key constraints ('simple', 'single recipient', 'no attachments'). It distinguishes from sibling tools like 'send_email' and 'send_email_with_custom_config' by emphasizing simplicity and limitations, though it doesn't explicitly name those alternatives.

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 context through the constraints '单个收件人，无附件' (single recipient, no attachments), suggesting this tool is for basic email needs. However, it does not explicitly state when to use this tool versus alternatives like 'send_email' or 'send_email_with_custom_config', nor does it provide any exclusions or prerequisites. The guidance is implied rather than direct.

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