Assistant Mail

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by AssistantMail

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Server Quality Checklist

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Latest release: v1.3.1
Disambiguation3/5
Most tools map cleanly to distinct resources and actions, but the four *_reference tools closely mirror operational tools like send_email, list_messages, get_message, and get_usage. The descriptions clarify that these are API documentation endpoints, but the names create real selection risk.
Naming Consistency4/5
The tools consistently use the assistantmail_ prefix with snake_case verb_noun names, and CRUD verbs are predictable. Minor deviations exist: 'health' lacks a verb, some object nouns are plural while others are singular, and the *_reference suffix is a distinct but somewhat unusual pattern.
Tool Count3/5
At 22 tools, the server is on the heavy side. The core operational tools are justified, but the four reference tools and metadata/health tools add bulk that could likely be consolidated or exposed as resources rather than first-class MCP tools.
Completeness4/5
The set covers mailbox lifecycle, message send/reply/delete/list/get workflows, recipient management, usage quotas, and inbound policy settings. Some possible features like drafts, read/unread state, or attachment handling are absent, but the primary email workflows appear usable without dead ends.
Average 3/5 across 22 of 22 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- 1 of 1 community issues answered or closed in the last 6 months
- 4 commits in the last 12 weeks
- Last stable release on September 3, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
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 does not mention authentication requirements, side effects, idempotency, possible failures, or what response to expect—only that a mailbox is created.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no redundant wording. It is concise and easy to parse, though its brevity sacrifices needed detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given three undocumented parameters, no annotations, and no output schema, this one-line description is far from complete enough to guide correct invocation. It states the high-level purpose but omits essential parameter semantics, usage context, and expected behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no information about the three parameters (apiKey, address, displayName). The agent cannot determine what values are expected or how they relate to the creation operation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Creates') and a clear resource ('a mailbox') with an explicit scope ('for the authenticated account'). It is easy to tell this from sibling tools like list/get/update/delete mailbox, though it does not 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.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to use this tool versus alternatives, nor any conditions or prerequisites. It only states what the tool does, leaving the agent to infer when it should be invoked.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing side effects and behavior. It says the tool 'provides' endpoint and headers, which hints at a read-only reference operation, but it does not clarify whether it makes a network call, returns static documentation, requires authentication, or has any 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no filler, which is good for conciseness. However, it is so terse that it sacrifices meaningful content; it is under-specified rather than efficiently complete.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema and no annotation coverage, so the description needed to clarify the return value, usage context, and relationship to sibling tools. It only gives a minimal hint about 'endpoint and required headers' and leaves critical operational questions unanswered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description needed to explain the mailboxId parameter but never mentions it. The parameter name is somewhat self-explanatory, but the agent receives no guidance on what the ID represents, where to obtain it, or how it relates to the returned endpoint and headers.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific resource ('AssistantMail REST endpoint and required headers') and ties it to email send requests, so it is not a pure tautology. However, it never states whether this tool actually sends emails or merely returns reference information, leaving the core action ambiguous relative to the sibling assistantmail_send_email.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to use this reference tool versus assistantmail_send_email or any other sibling. The phrase 'for email send requests' implies a connection to sending, but the description does not state that this tool should be used to retrieve endpoint/header details before calling the actual send tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. 'Gets' implies a read-only operation, but there is no mention of authentication requirements, error behavior, response shape, or what 'metadata' includes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It is concise, though the brevity sacrifices useful context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations and no output schema, the description leaves out important operational details such as return format, required authentication, and selection criteria versus sibling tools. A minimal single-lookup tool still needs more context for an agent to invoke it confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not compensate. It only restates that the mailboxId is an ID, which is already evident from the schema property name, and it does not explain the apiKey parameter at all.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action ('Gets') and resource ('mailbox metadata') for a specific mailbox ID. It distinguishes from list_mailboxes by implying a single mailbox lookup, though it doesn't explicitly name sibling alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to use this tool versus related tools like list_mailboxes, get_message, or get_me. The description only states what it does, not the conditions that should trigger its use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It discloses that both inbound and outbound messages are included, but doesn't state whether messages are returned in chronological order, whether the operation supports pagination, performance limits, or what happens with invalid mailbox IDs. The date filtering parameter 'since' implies behavior not described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the core purpose. It wastes no words, though it could add value with a second sentence about available filters without significant bloat.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters, 0% schema description coverage, no annotations, no output schema, and 21 sibling tools, this description is under-specified. It doesn't explain how results are ordered, whether the 'since' filter is applied to send or receive times, or how this relates to assistantmail_list_messages_reference. An agent cannot confidently build correct invocations from this alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 for the schema's lack of commentary. The description only describes mailbox scope and does not explain the semantics of 'limit', 'since', or 'apiKey'. The schema provides patterns but not meaning, so the description leaves substantial gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Lists') and resource ('inbound and outbound messages for a mailbox'), which clearly identifies the operation. However, it doesn't explicitly distinguish itself from sibling tools like assistantmail_list_messages_reference or assistantmail_get_message, so it gets a 4 rather than a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance about when to use this tool versus alternatives. It doesn't mention filtering options, pagination, or how it differs from the _reference variants. An agent would have to infer from names and schemas alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It only states that messages are listed; it does not mention pagination, response shape, authentication requirements, ordering, or what distinguishes this 'reference' variant behaviorally.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence and is easy to scan. It is appropriately short for a one-parameter tool, though it sacrifices useful differentiation for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool with no output schema and no annotations, the description is minimally adequate but incomplete. It leaves open the relationship to assistantmail_list_messages, the meaning of 'reference', and any behavioral details needed for a caller to trust the result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description should compensate for the undocumented mailboxId parameter. It only vaguely ties 'mailbox' to the operation and does not explain where the mailboxId comes from, its expected format, or how to obtain valid values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies a clear action and resource: listing messages (inbound and outbound) in a mailbox. However, it does not differentiate this tool from the closely named sibling assistantmail_list_messages, and the 'reference' suffix is left unexplained.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to choose this tool over assistantmail_list_messages or any other sibling. The description implies a listing use case but does not state conditions, alternatives, or exclusions needed for correct tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 does not mention whether the update is additive or replaces the entire policy, whether allowedSenders is required or optional for certain policy values, or any side effects (e.g., immediately affecting incoming mail routing). This is a significant gap for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single clear sentence with no filler. It is concise and front-loaded with the core action, though it sacrifices behavioral detail and parameter explanation for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is too sparse. An agent cannot know the full semantics of the policy values, the role of allowedSenders, or what happens after the update. Sibling tools like get_inbound_policy and update_mailbox exist, so a bit more contrast would help.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description names no parameters. The schema shows 'policy' with an enum and 'allowedSenders' as an array, but the description does not explain how these interact (e.g., whether allowedSenders is only relevant for the 'list' policy). The enum values 'owner', 'list', and 'sent' are left entirely unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Updates inbound email policy for the authenticated account' clearly identifies the verb ('updates'), resource ('inbound email policy'), and scope ('authenticated account'). It is specific enough to distinguish it from sibling tools like get_inbound_policy, though it does not explicitly name the sibling or elaborate on policy mechanics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, such as get_inbound_policy or update_mailbox. The description states what it does but gives no context about prerequisites, typical scenarios, or 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.
Behavior2/5
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 merely states that usage is fetched and does not disclose whether the operation is read-only, what limits or units are returned, or how quota periods are calculated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise, front-loaded sentence with no wasted words. It does not include extra guidance or alternatives, but it is efficiently structured for the limited content it provides.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter look-up tool, the description conveys the core purpose and the primary mailbox scope. However, with no output schema, no annotations, and no sibling differentiation, the agent is missing useful context about the return format, quota units, and when to choose the reference variant.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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, but it only loosely ties 'a mailbox' to the mailboxId parameter. It does not explain the apiKey parameter, its relationship to the request, or any mailboxId format requirements beyond what the schema already shows.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly names the verb ('Gets') and the resource ('daily and monthly send quota usage for a mailbox'), so the agent knows what the tool does. However, it does not differentiate this from the sibling assistantmail_get_usage_reference, so it falls short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. The description does not mention the sibling assistantmail_get_usage_reference or any conditions that would make one tool preferable, so the agent is left without routing help.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral disclosure burden. It indicates an informational behavior by saying it 'Provides the AssistantMail REST endpoint', but it does not disclose whether authentication is required, what the returned endpoint data looks like, whether network calls are made, or any limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no filler words or redundant content. It front-loads the core purpose and avoids restating the tool name or the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema and no annotations, so the description is the sole source of behavioral and return-value context. It fails to explain what exactly is returned when the endpoint is provided, how the mailboxId is applied, or any further invocation details, leaving an agent uncertain about the expected result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description makes no mention of the mailboxId parameter. The parameter name is somewhat self-explanatory, but the description adds no semantic detail about how mailboxId is used, what values are valid, or what happens if it is missing or invalid.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Provides') and names the resource ('the AssistantMail REST endpoint for checking send quota usage'), so an agent can tell the core function. However, it does not explicitly distinguish this 'reference' tool from its sibling assistantmail_get_usage, and it leaves ambiguous whether the tool returns endpoint documentation or performs the usage check.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to use this tool versus assistantmail_get_usage or any other alternative. The description implies a documentation/reference purpose, but it never states when an agent should select this tool instead of the non-reference sibling.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full behavioral burden. It only says 'Replies,' but does not disclose whether the reply is sent immediately, saved as a draft, requires specific auth, or what the response looks like. This is significant for a mutating tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler or redundancy. While it is somewhat under-specified for a full tool definition, its brevity and clarity on the basic action are strengths.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 5 parameters, no annotations, and no output schema, the description is too thin to be fully actionable. It omits key operational details such as body format requirements, authentication expectations, and return behavior, leaving important gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no parameter-level meaning. It does not explain the relationship between 'html' and 'text', the purpose of 'apiKey', or the exact roles of 'mailboxId' and 'messageId'. The agent is forced to infer everything from parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Replies') and resource ('existing message in a mailbox thread'), making the core action clear. It is distinguishable from siblings like assistantmail_send_email, which is for new messages, though it does not explicitly name the alternative.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'Replies to an existing message' implies the appropriate context for using this tool: responding within an existing thread. However, there is no explicit when-to-use guidance, no exclusions, and no mention of alternatives such as assistantmail_send_email.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. 'Queues' usefully discloses that sending is asynchronous rather than immediate, but it does not explain authentication requirements, side effects, error behavior, or whether the email may still fail after queuing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no filler, front-loading the action and object. It is as concise as possible.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 6 parameters, 3 required ones, no annotations, and no output schema, this one-line description is too thin. It omits body/parameter expectations, status/return semantics, and does not help distinguish this from related tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no information about any of the six parameters. The schema provides types and patterns, but the description contributes nothing to help an agent understand parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Queues') and names the resource ('an outbound email') and context ('for a mailbox'), making the core action clear. However, it does not explicitly differentiate from the sibling assistantmail_send_email_reference tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool instead of alternatives like assistantmail_reply_message or assistantmail_send_email_reference. No context, exclusions, or prerequisite conditions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses a meaningful non-obvious side effect: it may send a consent invitation. However, 'when required' is undefined, and with no annotations the description carries the full behavioral burden without covering duplicates, reversibility, or expected outcomes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with no filler. The consent-invitation clause adds important behavioral information without bloating the text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutating tool with no annotations and no output schema, this is minimal. It leaves unanswered the conditions for consent, whether apiKey is required, duplicate-recipient behavior, and what success or error looks like.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides no direct meaning for email or apiKey. 'Adds a recipient' weakly implies that email is the recipient address, but apiKey is entirely unexplained, and with 0% schema coverage the description needed to compensate more than it does.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: adding a recipient, plus the consent-invitation side effect. It is naturally distinguishable from sibling tools like remove_recipient and list_recipients, though it does not explicitly contrast them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives such as remove_recipient or send_email. It also does not mention prerequisites like apiKey or the consent policy context that determines when the invitation is required.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. 'Gets' implies a read-only operation, but the description does not clarify what the returned settings look like, whether defaults are included, or how authentication/authorization behaves beyond the vague 'authenticated account' phrasing. It is not contradictory, but it is thin.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. It names the action, resource, and scope efficiently, and every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter getter, the description covers the core purpose. However, the lack of an output schema and annotations means the agent is left without return-format expectations or explicit usage context, and the description does not differentiate it from related sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description never mentions the apiKey parameter or how it should be provided. Since the schema alone provides only a pattern and the description adds no parameter context, an agent receives no meaningful guidance for correctly supplying parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific action ('Gets'), resource ('inbound email policy settings'), and scope ('authenticated account'). This clearly distinguishes it from siblings like assistantmail_update_inbound_policy and assistantmail_get_me based on read-vs-write behavior and the target resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus its alternatives, such as assistantmail_update_inbound_policy for modifying settings or other getters for different resources. There is no mention of prerequisites, authentication flow, or contexts where this tool is preferable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 deletion happens, but does not warn about irreversibility, the destructive nature of deleting all messages, or what happens if both messageIds and deleteAll are supplied. For a deletion tool this is a significant transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the action and resource, then quickly covers both modes. It contains no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a potentially destructive tool with no annotations, no output schema, and zero schema description coverage, this description is too thin. It omits parameter relationships, safety warnings, return behavior, and edge cases such as providing both messageIds and deleteAll, making it incomplete for safe autonomous invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 vaguely maps the deletion modes to IDs and 'all', but it never names messageIds or deleteAll, and it does not explain how they interact, whether deleteAll is required for bulk deletion, or the role of apiKey. This leaves most parameter meaning undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear action ('Deletes messages'), the target resource ('a mailbox'), and two specific modes: by IDs or all messages. It distinguishes itself from sibling tools like assistantmail_delete_mailbox by explicitly focusing on messages rather than the mailbox itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to choose this tool over alternatives, nor does it mention exclusions or prerequisites. It only describes what the tool does, leaving the agent to infer appropriate usage from the tool name and sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosing behavior. It clearly indicates a read operation via 'fetching' and mentions full body content, but does not disclose endpoint-specific behavior, auth requirements, or response format beyond that.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one concise, front-loaded sentence that conveys the core function without extraneous detail. Every word contributes to understanding the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
It is adequate for a simple read operation with only two required parameters, but it lacks context about how this tool differs from the similarly named get_message sibling, and with no output schema it would benefit from a note about the response structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description does not explain the two parameters. The names mailboxId and messageId are fairly self-explanatory, but the description adds no meaning about how they are used together.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the operation: 'fetching a single message including its full body content.' It identifies the resource and scope, but does not differentiate from the sibling tool assistantmail_get_message, which appears to have the same purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus assistantmail_get_message or assistantmail_list_messages_reference. The description only states what it does, not when to prefer it over alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral disclosure burden. It states the update is currently limited to display name, but does not disclose whether the update is a full replacement, whether other metadata is preserved, what errors may occur, or any authorization/permission consequences.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one short sentence with no filler. The verb, resource, and current scope are front-loaded, making it immediately scannable for an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, important context is missing: when to use it, what the effect on existing metadata is, what the caller should expect in response, and whether apiKey is needed for authentication. The description is too thin to fully guide correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 by explaining parameters. It only clarifies displayName ('currently display name') and does not add meaning for mailboxId or apiKey, aside from what their names already imply.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Updates') and a clear resource ('mailbox metadata'), and narrows scope with '(currently display name)'. This distinguishes it from sibling tools like update_inbound_policy and from read/create/delete mailbox operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied: an agent can infer this tool is for changing a mailbox's display name. However, there is no explicit guidance about when to choose this over other mailbox tools, nor any when-not-to-use or alternative recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavior. 'Gets' implies a read-only operation and 'authenticated account' signals an auth requirement, but it does not describe error behavior, response format, or side effects beyond the obvious read nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. Every word contributes to conveying the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple and the description names both the subject and the returned metadata categories. However, with no output schema and no annotations, it would benefit from clarifying what 'tier metadata' includes, how authentication is handled, and whether the apiKey parameter is required or optional in practice.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention the apiKey parameter at all. The only parameter is left entirely to the schema's type and pattern, so the description fails to compensate for the missing parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Gets') and a precise resource ('account profile and tier metadata for the authenticated account'). This clearly distinguishes the tool from siblings like get_usage, mailbox operations, or policy tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no explicit when-to-use guidance, prerequisites, or comparison against alternatives. An agent can infer basic usage from the purpose, but there is no guidance on when to prefer this over sibling tools like assistantmail_get_usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the burden of explaining behavior. It states the operation and the authentication scope, which is useful. However, it does not disclose possible pagination, response format, ordering, or any side effects, though 'List' strongly implies a read-only operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single clear sentence with no wasted words. It states the action, resource, and scope immediately, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list operation with only one optional parameter, the description is minimally adequate: it tells the agent what the tool does and what scope it covers. However, because there is no output schema and no explanation of the parameter or response shape, the description is not fully complete for an agent that needs to process the returned mailbox data.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter, apiKey, with 0% schema description coverage, and the description does not mention it at all. Since the parameter is optional and the description provides no guidance on when to pass it or how it relates to the 'authenticated account,' the description fails to compensate for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb, 'Lists', and a specific resource, 'mailboxes', and clarifies scope with 'accessible to the authenticated account.' This clearly distinguishes the tool from siblings like create_mailbox, get_mailbox, update_mailbox, and delete_mailbox, which serve different actions on the same resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used when you need to enumerate the mailboxes associated with the authenticated account, but it does not explicitly state when not to use it or point to alternatives such as get_mailbox for a single mailbox. Usage context is inferred rather than directly provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description clearly discloses the core behavioral effect: a recipient is removed from the allowed recipient list. Since no annotations are provided, the description carries the full burden, but it does not mention side effects, whether the action is reversible, or any authorization needs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler or repeated information. It is appropriately terse, though it could safely add a bit more context without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutating tool with no annotations, no output schema, and no parameter descriptions, this is too thin. An agent can infer the basic operation, but it lacks guidance on the optional apiKey, the consequences of removal, and how this relates to the broader recipient-management workflow.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, so the description must compensate for both parameters. It only implies that the removed recipient corresponds to the email field, and it says nothing about the optional apiKey or when that parameter is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb, 'Removes', and a precise resource: 'a recipient from the allowed recipient list.' This cleanly separates it from sibling tools like add_recipient and list_recipients, making the tool's function immediately clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is implied by the action itself: use this tool when a recipient should no longer be on the allowed list. However, there is no explicit guidance about when not to use it, nor does it mention alternatives such as add_recipient for restoring access.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It discloses a key destructive side effect ('all associated messages' are deleted), which is valuable. However, it does not mention irreversibility, authentication requirements, or side effects on related entities such as recipients or policies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. Every word contributes to the tool's core behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive tool with no annotations and no output schema, the description is under-specified. It omits irreversibility, what happens on failure, and what output the agent should expect after deletion.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 0% description coverage, so the description must compensate. It provides only implied meaning for mailboxId through 'Deletes a mailbox' and says nothing about apiKey beyond what the schema pattern already conveys.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Deletes'), names the resource ('a mailbox'), and clarifies scope ('all associated messages'), distinguishing it from the sibling delete_messages tool which only removes messages without the mailbox.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool: when the entire mailbox and its messages should be removed. However, it does not explicitly state when not to use it, mention alternatives such as delete_messages for deleting only individual messages, or note prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It does reveal that text/html bodies are included only 'when available,' which is a meaningful caveat, but it does not explain failure behavior, response shape, or authentication requirements. Some transparency is present, but significant gaps remain.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It states the core action first and adds the key conditional detail about hydrated bodies. Every word contributes to understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema and no annotations, and the description does not explain what a caller should expect in the response beyond possibly hydrated bodies. It also leaves the 'when available' condition undefined and does not clarify whether metadata, headers, or other fields are returned. Given the ambiguity with get_message_reference, more detail is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 indirectly maps to mailboxId and messageId through 'mailbox' and 'specific message,' but it provides no detail on apiKey and gives no format or semantics beyond what the schema field names already imply. This is partial compensation at best.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Gets') and resource ('a specific message for a mailbox'), and the qualifier 'including hydrated text/html bodies when available' distinguishes it from sibling tools like list_messages and get_message_reference. This clearly tells an agent what the tool returns and sets it apart from related operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool: when you need a specific message and its hydrated bodies. However, it does not explicitly state when not to use it or mention alternatives such as get_message_reference, so the usage context remains implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It communicates a read-only listing behavior and an account scope, but it does not disclose response shape, pagination, whether apiKey must be supplied, or how authentication is established. Basic transparency is present, but richer behavioral detail is missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The entire description is one concise sentence with no filler, and the core action and scope are front-loaded. Every word contributes to understanding the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter list tool, the description covers the primary behavior, but without an output schema it should say more about what the returned recipient list contains and how authentication/apiKey is handled. It 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.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the apiKey parameter's role, optionality, or relationship to the authenticated account. The property name and regex pattern provide limited self-evident semantics, so this is not a 1, but the definition still fails to meaningfully document the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Lists') with a concrete resource ('approved/pending recipients') and scope ('for the authenticated account'), making the tool's purpose immediately clear. It is easily distinguished from sibling tools for mailboxes and messages, and the only other recipient tools are add/remove operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the usage context (inspect the recipient list for the current account) but offers no explicit guidance on when to choose this tool over add_recipient/remove_recipient or any other alternative. There are no exclusions or when-not-to-use instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It does communicate that the operation is read-only by saying 'Returns', which rules out destructive behavior. However, it does not clarify whether the tool performs a live health check, what metadata fields are included, or how failures are reported.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. Every word contributes meaning, and it is appropriately sized for a zero-parameter health/metadata tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is minimally viable: it names the tool's purpose well enough for an agent to select and invoke it. Yet without an output schema, it leaves the exact contents of 'metadata' ambiguous, so an agent cannot fully predict what the response will contain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and schema coverage is 100%, so there is no parameter semantics burden on the description. The baseline of 4 applies because no compensation is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a clear verb ('Returns') and names a specific resource ('AssistantMail MCP server and API endpoint metadata'). It is immediately distinguishable from sibling tools, which all operate on mailboxes, messages, or policies rather than server-level metadata.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used to inspect AssistantMail server/endpoint metadata, but it does not explicitly state when to use it or when an alternative would be better. There is no direct competing sibling, so the lack of exclusions is acceptable, but usage context is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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