Outlook MCP Server

by cqyefeng119

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes, with clear separation between email and calendar operations. However, some potential confusion exists between 'create_draft' and 'duplicate_email_as_draft', and between the various search tools (search_draft_emails, search_inbox_emails, search_sent_emails) which differ only by folder location rather than fundamental functionality.
Naming Consistency5/5
Excellent consistency with a clear verb_noun pattern throughout. All tools use snake_case and follow predictable naming conventions like 'get_', 'list_', 'create_', 'update_', 'delete_', 'search_', 'mark_', and 'summarize_' prefixes. The naming scheme is highly predictable and agent-friendly.
Tool Count4/5
20 tools is slightly high but reasonable for a comprehensive Outlook integration covering both email and calendar functionality. The count reflects the dual-domain nature of the server, though some consolidation might be possible (particularly among search operations).
Completeness5/5
Excellent coverage of both email and calendar domains. Email tools provide complete lifecycle management (create, read, search, mark, summarize) across multiple folders. Calendar tools cover event CRUD, availability checking, attendee management, and status setting. No obvious gaps exist for core Outlook workflows.
Average 2.7/5 across 20 of 20 tools scored. Lowest: 1.7/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
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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

Behavior1/5
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. The description only states what the tool does ('search') without any information about permissions needed, rate limits, pagination behavior, what fields are searched, or what the return format looks like. For a search tool with zero annotation coverage, this is completely inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise with just three words, this is a case of under-specification rather than effective conciseness. The description doesn't earn its place by providing meaningful guidance or context. It's too brief to be helpful, failing to convey necessary information about the tool's behavior or usage.
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 the lack of annotations, no output schema, and the presence of multiple similar sibling tools, the description is completely inadequate. It fails to explain what makes this tool distinct from other search and listing tools, doesn't describe the return format or behavior, and provides no context about limitations or appropriate usage scenarios.
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?
The input schema has 100% description coverage, with both parameters ('query' and 'count') well-documented in the schema itself. The description adds no additional parameter information beyond what's already in the schema. According to the scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Search sent emails' is a tautology that essentially restates the tool name. It does specify the verb 'search' and resource 'sent emails', but fails to distinguish this tool from sibling tools like 'search_draft_emails' or 'search_inbox_emails'. The purpose is minimally stated but lacks differentiation from similar tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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. There are multiple sibling search tools (search_draft_emails, search_inbox_emails) and listing tools (get_sent_emails) that serve similar purposes, but the description offers no context about when this specific search tool is appropriate versus those other options.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. The description reveals nothing about how the search works (full-text? metadata?), what permissions are required, whether results are paginated, what format they return, or any rate limits. For a search tool with zero annotation coverage, this is completely inadequate.
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 maximally concise at just three words. There's zero wasted language or unnecessary elaboration. While this conciseness comes at the expense of completeness, the description itself is perfectly structured and front-loaded.
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 that this is a search tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what kind of search is performed, what fields are searched, what the return format looks like, or any behavioral characteristics. The combination of sparse description and missing structured data leaves significant gaps for an AI agent.
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?
The description provides no parameter information beyond what's already in the schema. However, with 100% schema description coverage, the schema already documents both parameters ('query' and 'count') adequately. The baseline score of 3 is appropriate when the schema does all the parameter documentation work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Search draft emails' is a tautology that essentially restates the tool name. While it does specify the verb 'search' and resource 'draft emails', it lacks specificity about what kind of search is performed (e.g., content-based, metadata-based) and doesn't distinguish it from sibling tools like 'get_draft_emails' or 'search_inbox_emails' beyond the obvious resource difference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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. There's no mention of when this tool is appropriate versus 'get_draft_emails' (which likely retrieves all drafts without filtering) or 'search_inbox_emails' (which searches a different email folder). No context about prerequisites, limitations, or appropriate use cases is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. The description only states the basic action without revealing any behavioral traits such as whether this is a read-only operation, what permissions are required, how results are returned (e.g., format, pagination), or any rate limits. This leaves critical operational details unspecified for a search 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 extremely concise with just three words, front-loading the core action and resource. There is no wasted language or unnecessary elaboration, making it efficient for quick understanding. However, this conciseness comes at the cost of completeness, as noted in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a search operation with 2 parameters), lack of annotations, and no output schema, the description is incomplete. It fails to address key contextual elements like what the search covers (e.g., subject, body, sender), how results are structured, or error conditions. While the schema covers parameters, the overall context for effective tool use is insufficient.
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?
The input schema has 100% description coverage, with clear documentation for both parameters (query and count). The description adds no additional meaning beyond what the schema provides—it doesn't explain parameter interactions, search syntax, or result limitations. With high schema coverage, the baseline score of 3 is appropriate as the schema handles parameter documentation adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Search inbox emails' is a tautology that essentially restates the tool name. While it indicates the resource (inbox emails) and action (search), it lacks specificity about what distinguishes this tool from sibling search tools like search_draft_emails or search_sent_emails. The purpose is clear at a basic level but fails to differentiate from alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 this tool is appropriate (e.g., for searching received emails) versus when to use sibling tools like search_draft_emails or search_sent_emails. There's no indication of prerequisites, context, or exclusions, leaving the agent with no usage direction.
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 for behavioral disclosure but offers minimal information. 'Mark email as read' implies a state mutation operation, but doesn't specify whether this requires specific permissions, whether the change is reversible, what happens if the email is already marked as read, or what side effects might occur. For a mutation tool with zero annotation coverage, this is inadequate.
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 maximally concise with just three words that directly convey the core function. There's zero wasted language or unnecessary elaboration, making it efficiently front-loaded and easy to parse.
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 mutation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what 'read' means in context, whether the operation is idempotent, what permissions are required, or what the expected outcome looks like. Given the complexity of email state management and the lack of structured documentation, this description leaves critical 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?
The schema description coverage is 100% with the single parameter 'email_id' documented as 'Email ID'. The description adds no additional parameter information beyond what the schema already provides. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Mark email as read' is essentially a tautology that restates the tool name without adding meaningful specificity. While it clearly indicates the action (marking) and resource (email), it doesn't distinguish this from potential sibling operations like 'mark_email_as_unread' or provide any context about what 'read' means in this system.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance on when to use this tool versus alternatives. With sibling tools like 'get_email_by_id', 'get_inbox_emails', and various search functions, there's no indication of whether this should be used after retrieving an email, as part of a workflow, or what prerequisites might exist.
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. The description only states what the tool does ('Get draft emails list') without mentioning any behavioral traits like whether it's read-only, if it requires authentication, how results are ordered, pagination behavior, or error conditions. For a tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just three words, which is appropriate for a simple retrieval tool. It's front-loaded with the core purpose. However, it could be slightly more informative without sacrificing conciseness, such as specifying it retrieves a list rather than just stating 'Get draft emails list'.
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 the lack of annotations and output schema, the description is incomplete. It doesn't explain what the return value looks like (e.g., list format, email fields included), ordering, pagination, or error handling. For a tool that presumably returns data, the absence of output information combined with minimal behavioral disclosure makes this description inadequate.
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 100%, with the single parameter 'count' clearly documented in the schema as 'Number of draft emails to retrieve' with a default value of 10. The description doesn't add any parameter information beyond what's already in the schema. With high schema coverage and only one parameter, the baseline score of 3 is appropriate.
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 'Get draft emails list' clearly states the verb 'Get' and resource 'draft emails list', making the basic purpose understandable. However, it doesn't differentiate from sibling tools like 'search_draft_emails' or 'get_inbox_emails', leaving ambiguity about scope and filtering capabilities. The purpose is stated but lacks specificity about what kind of retrieval this performs.
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 alternatives like 'search_draft_emails' or 'get_inbox_emails'. The description doesn't mention any context, prerequisites, or exclusions for usage. While the name implies it's for draft emails specifically, there's no explicit comparison with similar tools in the sibling list.
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 full burden. It only states the action without disclosing behavioral traits like permissions needed, rate limits, sorting order (e.g., by date), pagination, or what 'inbox' means (e.g., unread vs. all). For a read operation with no annotations, this is insufficient.
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, efficient sentence with no wasted words. It's front-loaded and appropriately sized for a simple tool, though it could be more informative without sacrificing 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?
Given the tool's complexity (a read operation with one parameter) and lack of annotations or output schema, the description is incomplete. It doesn't explain return values, error conditions, or how it differs from similar tools, making it inadequate for full contextual understanding.
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 100%, with the single parameter 'count' documented as 'Number of emails to retrieve' with a default of 10. The description adds no additional meaning beyond the schema, so it meets the baseline of 3 for high coverage.
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 'Get inbox email list' states a basic purpose (verb 'get' + resource 'inbox email list'), but it's vague about scope and doesn't distinguish from sibling tools like 'get_draft_emails', 'get_sent_emails', or 'search_inbox_emails'. It lacks specificity about what constitutes 'inbox' or what 'list' includes.
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. With siblings like 'search_inbox_emails' and 'get_email_by_id', the description doesn't indicate if this is for bulk retrieval, recent emails, or default behavior, leaving usage ambiguous.
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 full burden but discloses minimal behavioral traits. It implies a read operation but doesn't specify permissions needed, rate limits, pagination, sorting order, or what data is returned (e.g., subject, sender, date). For a tool with no annotation coverage, this leaves critical behavioral aspects undocumented.
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 extremely concise at three words, with zero wasted language. It's front-loaded with the core action and resource. For a simple tool, this brevity is appropriate, though it may sacrifice completeness.
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 no annotations, no output schema, and a simple but underexplained tool, the description is incomplete. It doesn't address return values, error conditions, or how it differs from similar tools like 'search_sent_emails'. For a tool in a context with many siblings, more guidance is needed to ensure correct usage.
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 100%, with the single parameter 'count' well-documented in the schema. The description adds no parameter semantics beyond what the schema provides, but with high coverage, the baseline is 3. No additional context about parameter usage or constraints is given.
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 'Get sent emails list' states the basic action (get) and resource (sent emails list), but is vague about scope and format. It doesn't differentiate from sibling tools like 'search_sent_emails' or 'get_inbox_emails' beyond the obvious 'sent' focus. The purpose is understandable but lacks specificity about what constitutes the 'list' (e.g., metadata vs. 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 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. With sibling tools like 'search_sent_emails' available, the description doesn't explain if this is for simple retrieval versus filtered searching, or when to prefer one over the other. There's no mention of prerequisites, context, or exclusions.
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. 'Summarize inbox emails' implies a read-only operation that processes multiple emails, but it doesn't specify what 'summarize' entails (e.g., format, length, content focus), whether it requires authentication, or if there are rate limits. For a tool with no 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 extremely concise with just three words, making it front-loaded and efficient. Every word ('Summarize inbox emails') directly contributes to understanding the tool's purpose without any wasted text. This is appropriately sized for a simple tool.
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 the complexity (summarization of multiple emails), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the summarization returns (e.g., a list of summaries, a single aggregated summary), how emails are selected (e.g., most recent), or any constraints. For a tool with no structured behavioral or output information, the description should provide more context.
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?
The input schema has 100% description coverage, with the single parameter 'count' clearly documented as 'Number of emails to summarize' with a default of 10. The description doesn't add any meaning beyond what the schema provides (e.g., it doesn't explain how 'count' interacts with inbox size or ordering). With high schema coverage, the baseline score of 3 is appropriate.
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 'Summarize inbox emails' clearly states the verb ('summarize') and resource ('inbox emails'), making the basic purpose understandable. However, it doesn't distinguish this tool from its sibling 'summarize_email' (which appears to summarize individual emails) or 'get_inbox_emails' (which likely retrieves inbox emails without summarization). The purpose is clear but lacks sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 this summarization is appropriate compared to retrieving raw emails with 'get_inbox_emails' or summarizing individual emails with 'summarize_email'. There's also no indication of prerequisites, limitations, or context for usage.
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. 'Create new email draft' implies a write operation but lacks crucial details: whether it requires specific permissions, if drafts are saved automatically, what happens on failure, or any rate limits. This is inadequate for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it immediately scannable and appropriately sized for its purpose.
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 mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what happens after creation (e.g., where the draft is stored, if it returns an ID), behavioral constraints, or error conditions, leaving significant gaps for the agent.
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 100%, so the schema fully documents all parameters (to, subject, body, cc, bcc). The description adds no additional parameter information beyond what's in the schema, meeting the baseline expectation but not providing extra value.
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 'Create new email draft' clearly states the verb ('Create') and resource ('email draft'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'duplicate_email_as_draft' or 'get_draft_emails', which would require more specificity for 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. There's no mention of prerequisites, when to choose this over 'duplicate_email_as_draft', or any contextual constraints, leaving the agent with insufficient usage direction.
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 for behavioral disclosure. It states the tool creates events, implying a write/mutation operation, but doesn't mention authentication requirements, rate limits, whether events are immediately published to calendars, or what happens on failure. The example ('OutOfOffice for vacation') adds some context but doesn't cover critical behavioral aspects 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 extremely concise - a single sentence with a parenthetical example. It's front-loaded with the core purpose and wastes no words. Every element (the main action and the example) earns its place without 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 creation tool with 7 parameters, no annotations, and no output schema, the description is incomplete. It doesn't address what the tool returns (event ID? success status?), error conditions, or behavioral constraints. While the schema covers parameter details, the description lacks context about the operation's effects and outcomes that would help an agent use it correctly.
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 100%, so the schema already documents all 7 parameters thoroughly. The description adds minimal value beyond the schema: it emphasizes the 'showAs' parameter with an example ('OutOfOffice for vacation'), but doesn't provide additional semantic context about other parameters or their relationships. Baseline 3 is appropriate when schema does the heavy lifting.
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: 'Create a calendar event with specific Show As status'. It specifies the verb ('Create') and resource ('calendar event') with a distinguishing feature ('specific Show As status'). However, it doesn't explicitly differentiate from sibling tools like 'create_draft' or 'update_event' beyond the Show As focus.
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 minimal usage guidance. It mentions 'e.g., OutOfOffice for vacation' as an example, but doesn't specify when to use this tool versus alternatives like 'set_show_as' (which might modify existing events) or 'create_draft' (which might create events without immediate Show As settings). No explicit when/when-not instructions or prerequisite context 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 'Delete' implies a destructive mutation, the description doesn't specify whether this requires special permissions, if deletions are permanent or reversible, what happens to associated data (e.g., attendees), or any rate limits. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action ('Delete a calendar event') without unnecessary words. Every part of the sentence earns its place by specifying the resource and key parameter. There is zero waste 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?
Given the complexity of a destructive operation with no annotations and no output schema, the description is incomplete. It lacks critical context such as error handling, confirmation requirements, return values, or side effects. For a tool that permanently modifies data, this minimal description leaves too many unknowns for safe and effective use.
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 100%, so the schema already documents both parameters ('eventId' as required, 'calendar' as optional). The description mentions 'by its ID' which aligns with the 'eventId' parameter but adds no additional semantic context beyond what the schema provides. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't detract either.
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 ('Delete') and resource ('calendar event by its ID'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'update_event' or 'list_events', but the verb 'Delete' is specific enough to distinguish it as a destructive operation. This is not a tautology since it provides more information than just the tool name.
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 (e.g., needing an event ID from 'list_events' or 'get_calendars'), when not to use it (e.g., for read-only operations), or explicit alternatives among siblings like 'update_event'. The agent must infer usage from the tool name 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 of behavioral disclosure. It states that the tool duplicates an email 'as draft' and preserves 'complete format', which implies a read-and-copy operation without deletion. However, it lacks details on permissions needed, rate limits, error conditions, or what 'preserving complete format' entails (e.g., attachments, formatting). For a mutation tool with zero annotation coverage, this is insufficient.
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, efficient sentence: 'Duplicate existing email as draft (preserving complete format)'. It is front-loaded with the core action and includes a clarifying parenthetical. There is no wasted verbiage, making it highly concise and well-structured for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a mutation operation with 4 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't explain the return value, error handling, or behavioral nuances like whether the original email is affected. For a tool that creates drafts, more context is needed to guide effective use.
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 100%, meaning all parameters are documented in the input schema. The description adds no additional parameter semantics beyond implying that 'preserving complete format' might relate to how source_email_id is used, but it doesn't clarify parameter interactions or optionality beyond what the schema provides. With high schema coverage, a baseline score of 3 is appropriate.
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: 'Duplicate existing email as draft (preserving complete format)'. It specifies the verb ('duplicate'), resource ('existing email'), and outcome ('as draft'), which is specific and actionable. However, it doesn't explicitly distinguish this from sibling tools like 'create_draft' or 'get_draft_emails', which slightly reduces its clarity 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. It doesn't mention sibling tools like 'create_draft' for creating drafts from scratch or 'get_draft_emails' for retrieving existing drafts, nor does it specify prerequisites or exclusions. This leaves the agent without context for 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool finds available slots but doesn't explain key behaviors: whether it considers existing events, handles time zones, requires authentication, or has rate limits. For a read operation with no 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Find available time slots in the calendar.' It's front-loaded with the core purpose, with zero wasted words, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, no annotations, no output schema), the description is incomplete. It doesn't address behavioral aspects like how availability is determined, what the output format is, or prerequisites. For a tool that likely interacts with calendar data, more context is needed.
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?
The schema description coverage is 100%, so the schema already documents all 6 parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema, such as explaining how 'calendar' interacts with availability or default behaviors. Baseline 3 is appropriate when the schema does the heavy lifting.
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: 'Find available time slots in the calendar.' It specifies the verb ('find') and resource ('available time slots'), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'list_events' or 'get_calendars,' which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 sibling tools like 'list_events' or explain scenarios where this tool is preferred, such as for scheduling meetings versus viewing events. This lack of context leaves the agent to infer usage.
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 states the tool checks attendee status, implying a read-only operation, but does not specify if it requires authentication, has rate limits, returns structured data, or handles errors. This leaves significant gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy to understand quickly.
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 the lack of annotations and output schema, the description is incomplete. It does not explain what the tool returns (e.g., status types like 'accepted' or 'declined'), error conditions, or dependencies on other tools. For a tool with no structured behavioral data, more context is needed to be fully helpful.
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?
The schema description coverage is 100%, with clear descriptions for 'eventId' and 'calendar'. The description adds minimal value beyond the schema, as it does not explain parameter interactions or provide examples. With high schema coverage, the baseline score of 3 is appropriate, as the description does not compensate with additional insights.
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 as 'Check the response status of meeting attendees,' which includes a specific verb ('Check') and resource ('meeting attendees'). It distinguishes itself from siblings like 'list_events' or 'get_calendars' by focusing on attendee statuses, but does not explicitly differentiate from all siblings (e.g., 'get_email_by_id' is unrelated).
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 does not mention prerequisites, such as needing an event ID, or compare it to similar tools like 'list_events' for broader event details. Usage is implied through the parameter 'eventId' but not explicitly stated.
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 but offers minimal insight. It implies a read-only operation ('Get') but doesn't specify permissions required, rate limits, error handling (e.g., for invalid IDs), or output format. For a tool with zero annotation coverage, this is inadequate, though not contradictory.
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 extremely concise with a single sentence ('Get specific email by ID'), which is front-loaded and wastes no words. Every part of the sentence contributes directly to the tool's purpose, making it efficient and easy to parse, though this conciseness comes at the cost of detail in other dimensions.
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 the tool's low complexity (one parameter, no nested objects) but lack of annotations and output schema, the description is incomplete. It doesn't address behavioral aspects like what data is returned or error conditions, leaving gaps for the agent. For a read operation with no structured output guidance, more context is needed to be fully helpful.
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 100%, with the parameter 'id' documented as 'Email ID'. The description adds no additional meaning beyond this, such as format examples (e.g., UUID) or sourcing hints. Since the schema fully describes the single parameter, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't detract either.
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 'Get' and resource 'specific email by ID', making the purpose unambiguous. It distinguishes from sibling tools like get_inbox_emails or get_sent_emails by specifying retrieval of a single email via ID. However, it doesn't explicitly mention what 'get' entails (e.g., fetch metadata, content, or both), which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 (e.g., needing a valid email ID), contrast with search tools (e.g., search_inbox_emails), or specify use cases like retrieving a known email versus browsing. This lack of context leaves the agent without clear usage direction.
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 action ('List') but doesn't mention whether this is a read-only operation, what permissions are required, how results are returned (e.g., pagination), or any rate limits. This is inadequate for a tool that likely accesses user data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core functionality without unnecessary words. Every part ('List calendar events within a specified date range') directly contributes to understanding the tool's purpose, making it optimally concise.
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 the lack of annotations and output schema, the description is incomplete. It doesn't address behavioral aspects like safety, permissions, or result format, which are critical for a tool that lists personal calendar events. For a 3-parameter tool with no structured safety hints, this description leaves significant 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?
The description mentions 'date range' which aligns with the 'startDate' and 'endDate' parameters in the schema, but adds no additional meaning beyond what the schema already provides (100% coverage). It doesn't explain the 'calendar' parameter's purpose or how date ranges are interpreted, so it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 ('calendar events') with scope ('within a specified date range'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'find_free_slots' or 'get_calendars', which also deal with calendar data but serve different purposes.
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 'find_free_slots' (for availability) or 'get_calendars' (for calendar metadata). It lacks any mention of prerequisites, exclusions, or typical use cases, leaving the agent to infer usage from context 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 states this is a mutation tool ('Set'), implying it modifies data, but doesn't disclose behavioral traits like required permissions, whether changes are reversible, error handling, or rate limits. This is a significant gap for a tool that updates calendar events.
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, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of updating calendar events, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral aspects, error cases, or return values, which are crucial for an agent to use this tool effectively in a real-world context.
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 100%, so the schema already documents all parameters thoroughly. The description adds no additional meaning beyond what's in the schema, such as explaining parameter interactions or constraints. The baseline score of 3 reflects adequate but minimal value added by the description.
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 ('Set') and resource ('Show As status for a calendar event'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'update_event' or 'create_event_with_show_as', which might have overlapping functionality.
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 'update_event' or 'create_event_with_show_as'. It doesn't mention prerequisites, exclusions, or specific contexts, leaving the agent to infer usage from the tool name 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 what the tool does but doesn't describe how it works—for example, whether it generates a new summary each time, what format or length the summary has, or if it requires specific permissions. For a tool with zero 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse. Every word earns its place, and there's no redundancy or fluff.
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 the lack of annotations and output schema, the description is incomplete for a tool that performs a non-trivial operation like summarization. It doesn't explain what the summary output looks like, any limitations (e.g., length, language), or error conditions. For a tool with no structured output documentation, the description should provide more context about the result.
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?
The input schema has 100% description coverage, with the single parameter 'email_id' clearly documented. The description doesn't add any meaning beyond the schema, such as explaining what constitutes a valid email ID or where to obtain it. However, with high schema coverage and only one parameter, the baseline score of 3 is appropriate as the schema handles the documentation adequately.
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 ('Summarize') and resource ('individual email content'), making the purpose immediately understandable. It doesn't explicitly differentiate from the sibling 'summarize_inbox' tool, which appears to summarize multiple emails, but the focus on 'individual' provides some distinction. The description avoids tautology by specifying the action beyond just the tool name.
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 the sibling 'summarize_inbox' tool for bulk summarization or clarify prerequisites like needing an email ID. There's no indication of when this tool is appropriate versus simply reading the email with 'get_email_by_id'.
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 for behavioral disclosure. 'Update an existing calendar event' implies mutation but doesn't specify what happens with partial updates, whether changes are reversible, permission requirements, or rate limits. This is inadequate for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized and front-loaded with the core functionality.
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 mutation tool with 9 parameters, no annotations, and no output schema, the description is insufficient. It doesn't address behavioral aspects like error conditions, partial update behavior, or what the tool returns. The 100% schema coverage helps with parameters but doesn't compensate for missing operational context.
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 100%, so all parameters are documented in the schema. The description doesn't add any meaningful parameter semantics beyond what's already in the schema (e.g., it doesn't explain relationships between date/time parameters or provide usage examples). Baseline 3 is appropriate when schema does the heavy lifting.
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 ('Update') and target resource ('an existing calendar event'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'set_show_as' or 'duplicate_email_as_draft' which might also modify events in some way.
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 alternatives. The description doesn't mention prerequisites (e.g., needing an existing event ID), exclusions, or when other tools like 'create_event_with_show_as' or 'delete_event' would be more appropriate.
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 full burden for behavioral disclosure. 'List available calendars' implies a read-only operation but doesn't specify permissions needed, pagination behavior, rate limits, or what 'available' means (e.g., user-accessible vs. all system calendars). This leaves significant gaps for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It's front-loaded with the core action and resource, making it immediately understandable without unnecessary elaboration.
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 zero parameters and no output schema, the description is minimally adequate but incomplete. It lacks details on what 'available calendars' includes (e.g., personal vs. shared), return format, or error conditions, which are important for a read operation with no annotations to provide context.
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 description coverage is 100%, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, earning a high baseline score since it doesn't need to compensate for any 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 'List available calendars' clearly states the verb ('List') and resource ('available calendars'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list_events' or 'find_free_slots' that also involve calendar-related operations, preventing 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. With siblings like 'list_events' and 'find_free_slots' that operate on calendars, there's no indication whether this tool is for metadata listing, event enumeration, or other purposes, leaving usage context ambiguous.
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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