Himalaya MCP Server

by andasv

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
Most tools have distinct purposes, but there is some overlap between envelope_thread and message_thread that could cause confusion. Both tools involve retrieving message threads, though envelope_thread focuses on structure while message_thread returns full messages. Other tools like account_list, folder_list, and attachment_download are clearly distinct.
Naming Consistency4/5
The naming follows a consistent pattern with underscores separating words (snake_case). However, there is a minor inconsistency: most tools use a verb_noun format (e.g., account_list, envelope_list), but template_forward, template_reply, and template_write use a noun_verb format, which slightly deviates from the overall convention.
Tool Count5/5
With 10 tools, the count is well-suited for an email management server. It covers essential operations like listing accounts and folders, reading messages, handling attachments, and generating email templates, without being overwhelming or too sparse for the domain.
Completeness4/5
The tool set provides good coverage for email reading, organization, and template generation, but lacks explicit tools for sending emails (e.g., a send_message tool) or managing drafts beyond templates. While template_send is mentioned in a description, it's not included as a tool, creating a minor gap in the email lifecycle.
Average 3.5/5 across 10 of 10 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- 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.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states that 'Attachments are saved to the current working directory,' which adds useful context about file system impact. However, it lacks details on permissions needed, error handling, rate limits, or what happens if attachments are large or numerous. For a tool that writes files, 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized. It starts with the core purpose, adds behavioral context in the second sentence, and lists parameters with brief explanations. Each sentence earns its place, and it's front-loaded with the main action. A minor deduction for slightly verbose parameter formatting, but overall efficient.
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?
Given 3 parameters with 0% schema coverage and no annotations, the description provides basic parameter semantics and some behavioral context (file saving location). An output schema exists, so return values don't need explanation. However, for a tool that downloads files, more details on file naming, overwrite behavior, or error cases would improve completeness. It's minimally viable but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 provides brief explanations for each parameter: 'envelope_id: The envelope/message ID,' 'folder: Folder name. Defaults to INBOX,' and 'account: Account name. If omitted, uses the default account.' This adds basic meaning beyond the schema's titles, but doesn't cover formats, constraints, or examples. With 3 parameters and low schema coverage, this is adequate but minimal.
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 tool's purpose: 'Download all attachments from a message.' It specifies the verb ('download') and resource ('attachments from a message'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'message_read' or 'envelope_list', which might also involve message operations, so it doesn't reach 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.
Usage Guidelines2/5
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 mentions parameters like 'folder' and 'account' with defaults, but doesn't explain scenarios where you'd choose this over other tools (e.g., 'message_read' for viewing content without downloading). There's no mention of prerequisites or exclusions, leaving usage context implied at best.
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. It states the action ('List all folders/mailboxes') but lacks behavioral details such as permissions required, rate limits, pagination, or what 'all' entails (e.g., recursive listing, depth). This leaves gaps in understanding how the tool behaves beyond its basic function.
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 appropriately sized and front-loaded, with the main purpose stated first and parameter details in a separate 'Args' section. It avoids unnecessary words, but the structure could be slightly improved by integrating parameter info more seamlessly. Overall, it's efficient with minimal waste.
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?
Given the tool's low complexity (1 optional parameter) and the presence of an output schema (which handles return values), the description is mostly adequate. However, it lacks behavioral context (e.g., listing scope, permissions) and usage guidelines, which are minor gaps. It covers the basics but could be more complete for optimal agent use.
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?
Schema description coverage is 0%, so the description must compensate. It adds meaning by explaining the 'account' parameter: 'Account name. If omitted, uses the default account.' This clarifies the optional nature and default behavior, which is valuable beyond the schema's basic type and title. With only one parameter, this is sufficient for good understanding.
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 verb ('List') and resource ('folders/mailboxes for an email account'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'account_list' or 'envelope_list', which might list different resources, so it doesn't fully distinguish itself in context.
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 provides no guidance on when to use this tool versus alternatives, such as how it differs from 'account_list' or other listing tools. It mentions the default behavior for the 'account' parameter, but this is parameter-specific and not usage context. No explicit when/when-not or alternative tool references are included.
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. It mentions the default return (plain text body) and parameter effects (headers, raw), but lacks critical behavioral details: it doesn't specify error handling (e.g., if envelope_id is invalid), permissions required, rate limits, or whether the operation is idempotent. For a read tool with zero annotation coverage, this is a significant gap.
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 appropriately sized and front-loaded: the first sentence states the purpose, followed by return behavior and parameter details. Each sentence adds value, with no redundancy. However, the parameter list could be more integrated into prose for better flow, though it remains efficient.
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?
Given the complexity (5 parameters, 0% schema coverage, no annotations, but with an output schema), the description is moderately complete. It covers parameters well and mentions the default return, but lacks behavioral context like error handling or permissions. The output schema likely details return values, so the description doesn't need to explain returns, but overall gaps remain for a tool with multiple parameters and no annotations.
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?
Schema description coverage is 0%, so the description must compensate. It adds meaningful semantics for all 5 parameters: envelope_id is the ID to read, folder defaults to INBOX, account uses default if omitted, headers includes message headers, and raw returns MIME content. This goes beyond the schema's titles (e.g., 'Folder' vs 'Folder name. Defaults to INBOX'), providing clear usage context.
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 tool's purpose: 'Read a message by its envelope ID' specifies the verb (read) and resource (message). It distinguishes from siblings like message_thread (which handles threads) and envelope_list (which lists envelopes). However, it doesn't explicitly differentiate from all siblings, such as template_forward or template_reply, which are write operations.
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 provides no guidance on when to use this tool versus alternatives. It doesn't mention when to prefer message_read over message_thread for single messages, or when to use envelope_list for listing instead. There's no context about prerequisites or exclusions, leaving the agent to infer usage from the purpose 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 full burden. It mentions the tool generates/returns a template but doesn't disclose behavioral traits such as whether it's read-only or mutative, what permissions are needed, how it handles errors, or any rate limits. The description is minimal and 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the purpose, followed by return details and parameter explanations. It's efficient with no wasted sentences, though the parameter section could be more integrated for better flow.
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?
Given 3 parameters with 0% schema coverage and an output schema exists, the description partially compensates by explaining parameters but lacks behavioral context. It's adequate for basic understanding but incomplete for safe and effective use, as it doesn't cover error handling, permissions, or interaction with siblings.
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?
Schema description coverage is 0%, so the description must compensate. It adds meaningful semantics: envelope_id is for 'The envelope/message ID to forward,' folder is 'Folder name' with a default, and account is 'Account name' with a default if omitted. This clarifies parameter roles beyond schema titles, though it doesn't detail format constraints or examples.
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 tool's purpose: 'Generate a forward template for a message' and 'Returns an MML template pre-filled with forwarded message content.' It specifies the verb (generate/return) and resource (forward template/MML template), though it doesn't explicitly differentiate from sibling tools like template_reply or template_write beyond the 'forwarded' context.
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 usage when forwarding a message by referencing 'forwarded message content,' but it doesn't explicitly state when to use this tool versus alternatives like template_reply or template_write. No guidance on prerequisites or exclusions is provided.
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. While it mentions what the tool returns ('MML template pre-filled with reply headers and quoted original message'), it doesn't describe important behavioral aspects like whether this is a read-only operation, what permissions are required, whether it modifies any data, or how errors are handled. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.
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 well-structured and appropriately sized. The first sentence states the core purpose, followed by what it returns, then parameter explanations. Each sentence adds value without redundancy. It could be slightly more concise by combining some parameter explanations, but overall it's efficient and front-loaded with the most important information.
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?
Given that there's an output schema (which handles return value documentation) and no annotations, the description provides adequate basic context about what the tool does and what parameters mean. However, for a tool that generates templates (potentially involving message composition and quoting), it lacks information about behavioral constraints, error conditions, or integration with sibling tools. The presence of an output schema elevates the baseline, but more behavioral context would be beneficial.
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?
With 0% schema description coverage, the description provides valuable semantic context for all 4 parameters beyond just their names. It explains that envelope_id is 'The envelope/message ID to reply to', folder 'defaults to INBOX', account 'uses the default account' if omitted, and reply_all controls whether to 'reply to all recipients'. This adds meaningful interpretation that the schema alone doesn't provide, though it doesn't cover all possible parameter nuances.
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 tool's purpose: 'Generate a reply template for a message' with specific details about what it returns ('MML template pre-filled with reply headers and quoted original message'). It distinguishes from sibling tools like template_forward and template_write by focusing specifically on reply generation. However, it doesn't explicitly contrast with message_thread or envelope_thread which might also involve message replies.
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 usage context through the parameter explanations (e.g., 'The envelope/message ID to reply to'), suggesting this tool is used when you have a specific message to reply to. However, it doesn't provide explicit guidance on when to use this versus alternatives like template_forward or template_write, nor does it mention prerequisites or when-not-to-use scenarios.
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. It states the tool returns a list with name, backend type, and default status, which is helpful. However, it doesn't disclose behavioral traits like whether this requires authentication, rate limits, error conditions, or pagination. The description adds some value but leaves gaps.
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 appropriately sized and front-loaded: the first sentence states the purpose, the second explains returns, and the third clarifies the parameter. Every sentence earns its place with no wasted words, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one optional parameter) and the presence of an output schema (which handles return values), the description is mostly complete. It covers purpose, returns, and parameter semantics. However, it lacks behavioral context like authentication needs, which holds it back from a 5.
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?
Schema description coverage is 0%, so the description must compensate. It explains the 'account' parameter as 'Optional specific account name to query', adding meaning beyond the schema's generic 'Account' title. With only one parameter well-explained, it effectively compensates for the schema gap, earning a 4.
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 tool's purpose: 'List all configured email accounts' (verb+resource). It distinguishes from siblings like 'folder_list' or 'envelope_list' by focusing on accounts rather than folders or messages. However, it doesn't explicitly differentiate from 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.
Usage Guidelines2/5
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 prerequisites, when not to use it, or how it relates to sibling tools like 'envelope_list' or 'folder_list'. The agent must infer usage from the purpose 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'Get thread view' and 'Shows the conversation thread structure', implying a read-only operation, but does not specify whether it requires authentication, has rate limits, returns paginated results, or handles errors. For a 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first sentence, followed by a clarifying sentence, then parameter details in a structured Args section. Every sentence adds value without redundancy, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, 1 required), no annotations, and the presence of an output schema (which handles return values), the description is largely complete. It covers purpose and parameter semantics well, but lacks behavioral details like authentication needs or error handling, which are important for a tool with zero annotation coverage.
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?
Schema description coverage is 0%, so the description must compensate. It provides clear semantics for all three parameters: envelope_id as 'The envelope/message ID', folder as 'Folder name' with a default, and account as 'Account name' with a default. This adds meaningful context beyond the schema's bare titles, though it could elaborate on format constraints (e.g., ID structure, valid folder names).
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 clearly states the verb 'Get thread view' and specifies the resource 'for a specific envelope', distinguishing it from sibling tools like envelope_list (which lists envelopes) and message_thread (which appears to handle threads differently). It further clarifies 'Shows the conversation thread structure for the given message', making the purpose specific and unambiguous.
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 provides no guidance on when to use this tool versus alternatives like message_thread or envelope_list. It mentions default values for optional parameters but offers no context about prerequisites, typical use cases, or exclusions, leaving the agent to infer usage based on parameter names 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?
With no annotations provided, the description carries full burden but only states it 'returns all messages in the conversation thread.' It doesn't disclose behavioral traits like pagination, rate limits, authentication needs, error conditions, or what 'full message thread' entails (e.g., metadata, attachments).
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 appropriately sized with clear front-loading of purpose. The Args section is well-structured but could be more integrated. No wasted sentences, though some behavioral context is missing.
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?
Given 3 parameters with 0% schema coverage and an output schema exists, the description adequately covers parameter semantics but lacks behavioral context for a read operation. It's minimally viable but leaves gaps about thread structure and operational constraints.
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?
Schema description coverage is 0%, but the description provides meaningful context for all 3 parameters: envelope_id identifies the thread, folder defaults to INBOX, and account defaults to default account. This compensates well for the lack of schema descriptions.
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 clearly states the specific action ('Read a full message thread') and resource ('by envelope ID'), distinguishing it from siblings like message_read (single message) and envelope_thread (different resource). The verb 'read' precisely indicates the operation.
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 usage when needing a full conversation thread rather than a single message, but doesn't explicitly state when to use this vs. alternatives like envelope_thread or message_read. No exclusions or prerequisites are mentioned.
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 full burden. It discloses key behavioral traits: returns sender, subject, date, flags without downloading full bodies, and mentions pagination. However, it doesn't cover rate limits, authentication requirements, error conditions, or what happens with invalid parameters.
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?
Perfectly structured with purpose statement first, then behavioral context, then parameter details in clear bullet format. Every sentence earns its place with no redundancy or wasted words. The parameter explanations are efficiently formatted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters with 0% schema coverage and no annotations, the description does an excellent job explaining parameter semantics. Since there's an output schema, the description correctly doesn't explain return values. The main gap is lack of behavioral context around authentication, errors, and rate limits.
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?
Schema description coverage is 0%, so the description must compensate. It provides meaningful context for all 5 parameters: folder name with example and default, account name with default behavior, pagination parameters with starting value, and query syntax specification. This adds substantial value beyond the bare schema.
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 clearly states the specific action ('List message envelopes'), the resource ('in a folder'), and distinguishes from siblings by specifying it returns headers only without full bodies. This differentiates it from tools like message_read that would retrieve full content.
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 usage for listing message metadata rather than full content, but doesn't explicitly state when to use this vs alternatives like message_read or envelope_thread. It mentions the default folder and account behavior, but lacks explicit guidance on tool selection scenarios.
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. It discloses that this generates a new template (creation behavior) and explains the MML format context, but doesn't mention permissions needed, rate limits, or what happens if the account doesn't exist. It adds some behavioral context but leaves gaps for a creation tool.
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 efficiently structured with purpose first, then return value explanation, then parameter details. Every sentence adds value: format explanation, connection to sending, and parameter semantics. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (so return values are documented elsewhere), 2 parameters with good semantic coverage in the description, and no annotations, the description is quite complete. It explains purpose, usage context, and parameters well. The only minor gap is lack of behavioral details like permissions or error cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by explaining both parameters: 'account' (default behavior when omitted) and 'headers' (format and example). It adds meaningful context beyond the bare schema, especially the headers format example which is crucial for correct usage.
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 clearly states the verb ('Generate') and resource ('new email template'), specifies the format ('MML format'), and distinguishes it from siblings by mentioning template_send. It goes beyond just restating the name to explain what the tool actually produces.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context about when to use this tool ('Returns a blank email template that can be filled in and sent via template_send'), but doesn't explicitly state when NOT to use it or mention alternatives among the sibling tools. The connection to template_send is helpful guidance.
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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