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 describes the return format (sender, subject, date, messageId, folderId) which is helpful, but doesn't address important behavioral aspects like pagination, sorting order, authentication requirements, rate limits, or error conditions. The description adds some value but leaves significant gaps for a tool that presumably accesses user data.

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 sentence that efficiently communicates the core functionality and return format. Every word earns its place, with no wasted verbiage. The information is front-loaded and immediately useful.

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 read-only list tool with no annotations and no output schema, the description provides basic functionality but lacks important context. It doesn't explain the 'recent' timeframe, sorting behavior, or what happens when count exceeds available messages. The return fields are listed, but without an output schema, the agent doesn't know data types or structure. The description is minimally adequate 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 input schema has 100% description coverage, with the single parameter 'count' clearly documented in the schema. The description doesn't add any parameter information beyond what's already in the schema. According to the 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 ('List recent inbox messages') and specifies the resource ('inbox messages'), making the purpose immediately understandable. However, it doesn't explicitly differentiate this tool from its sibling 'search_emails' tool, which might also return messages. The description specifies the returned fields (sender, subject, date, messageId, folderId), which helps clarify scope but doesn't fully distinguish from 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 provides no guidance on when to use this tool versus its sibling tools like 'search_emails' or 'read_email'. There's no mention of use cases, prerequisites, or exclusions. The agent must infer usage from the tool name and description alone without explicit contextual 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 full burden. It states the tool reads email bodies but doesn't disclose behavioral traits like whether it requires specific permissions, if it's a read-only operation, what happens if IDs are invalid, or if there are rate limits. The description is minimal and lacks essential operational context for a tool that accesses email data.

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 purpose and includes necessary contextual information about parameter sources. Every word serves a purpose with zero waste, making it appropriately sized for this simple 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?

Given the tool's low complexity (2 required parameters, no output schema, no annotations), the description is adequate but minimal. It covers the basic purpose and parameter sources but lacks information about return values, error conditions, or behavioral constraints. For a read operation without annotations, more context about what 'read' entails would be beneficial.

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 both parameters clearly documented in the schema. The description adds marginal value by reinforcing that both parameters come from list_inbox and search_emails, but doesn't provide additional semantic context beyond what's already 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 verb 'read' and the resource 'full body of an email', making the purpose specific and understandable. It distinguishes from siblings by specifying it's for reading individual emails rather than listing/searching (list_inbox, search_emails) or sending (send_email). However, it doesn't explicitly contrast with all siblings in a single statement.

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 for when to use this tool: after obtaining messageId and folderId from list_inbox or search_emails. This implicitly distinguishes it from send_email and gives prerequisites. However, it doesn't explicitly state when NOT to use it or name alternatives for similar tasks.

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 discloses that the tool returns messageId and folderId for use with read_email, adding useful context about output format and integration. However, it lacks details on behavioral traits like pagination, error handling, or rate limits, which are important for a search tool with no annotations.

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, consisting of a single, efficient sentence that conveys the core purpose, parameters, and output. Every part earns its place with no wasted words, making it highly concise and well-structured.

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 moderate complexity (search with two parameters), no annotations, and no output schema, the description is somewhat complete but has gaps. It explains the purpose and output format but lacks details on behavioral aspects like limits or errors. It's adequate but not fully comprehensive for a tool without structured support.

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 both parameters fully. The description adds no additional meaning beyond what the schema provides (e.g., it repeats the query parameter's purpose without new details). This meets the baseline of 3 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 tool's purpose with specific verbs ('search inbox') and resources ('emails'), and distinguishes it from siblings by specifying it searches by keyword, sender email, or subject fragment. It explicitly mentions the output format (messageId and folderId) and its intended use with read_email, making it highly specific and differentiated.

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 for when to use this tool (searching by specific criteria) and implies an alternative (list_inbox for listing without search). However, it does not explicitly state when not to use it or compare it to all siblings (e.g., send_email), keeping it at a 4 rather than 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the sender address configuration, which adds some context about authentication needs, but fails to cover critical traits: it doesn't specify whether this is a synchronous or asynchronous operation, potential rate limits, error handling, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

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 purpose without unnecessary words. Every element ('Send an email', 'from the configured ZOHO_SENDER address') earns its place by clarifying scope and constraints. There's zero waste or redundancy, 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 complexity of an email-sending tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral aspects (e.g., delivery confirmation, error responses), usage context, and output expectations. While the schema covers parameters well, the overall context for safe and effective use is insufficient, especially for a mutation 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 schema description coverage is 100%, with clear descriptions for all three parameters (to, subject, content). The description adds no parameter-specific information beyond what the schema provides, such as format examples or constraints. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 ('Send an email') and specifies the resource ('from the configured ZOHO_SENDER address'), making the purpose immediately understandable. It distinguishes from siblings like list_inbox or read_email by focusing on sending rather than retrieving emails. However, it doesn't explicitly differentiate from potential non-sibling alternatives like 'send_bulk_email' or 'schedule_email', which prevents 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 alternatives. It doesn't mention sibling tools like search_emails for finding emails before sending, or specify prerequisites such as needing a configured sender address. There's no indication of when not to use it (e.g., for bulk operations) or contextual triggers, leaving usage entirely implicit.

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