Claude-Read-Outlook-Attachments
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation4/5
Tools are mostly distinct: auth_status and begin_auth handle authentication, health_check monitors server, list_recent_messages finds emails, list_email_attachments shows attachments for a specific email, and read_email_attachment downloads/parses attachments. However, list_recent_messages and list_email_attachments could be confused if descriptions are glossed over, as both relate to emails and attachments.
Naming Consistency3/5Naming patterns are mixed: some tools start with verbs (begin_auth, list_recent_messages, list_email_attachments, read_email_attachment) while others are nouns (auth_status, health_check). The verb+noun pattern is not consistently applied, reducing predictability.
Tool Count5/5With 6 tools, the server is well-scoped for its purpose. It covers authentication (begin_auth, auth_status), server health (health_check), email discovery (list_recent_messages), attachment listing (list_email_attachments), and attachment reading (read_email_attachment). No extraneous tools.
Completeness4/5The tool surface covers the core workflow: authenticate, find emails with attachments, list attachments, and read them. Minor gaps include lack of tools for getting email metadata beyond attachments or searching other folders, but these are acceptable for an attachment-focused server.
Average 3.6/5 across 6 of 6 tools scored. Lowest: 2.7/5.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 2 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose behavioral traits such as pagination, limits, or whether it returns metadata vs. content. The agent has no insight into side effects or safety.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (one sentence) but lacks structure. It is too minimal, omitting critical information that could be front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of annotations, output schema, and parameter descriptions, the single sentence is insufficient. More context about usage and return value is necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain what the messageId parameter represents or the significance of the mailbox parameter (default 'me'). Elaboration on these is needed for correct usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List') and resource ('attachments for a specific Outlook email'). It distinguishes from sibling tools like list_recent_messages (lists emails) and read_email_attachment (reads a single attachment).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., needing a messageId from list_recent_messages) or when to use read_email_attachment instead.
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?
Without annotations, description carries full burden. It discloses default search location and preference for attachments, but omits auth needs, rate limits, pagination, and behavior of 'recent'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no redundant words. Clear structure, though 'prefers' is slightly ambiguous.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers core functionality but lacks details on return format, error handling, and auth. Given 6 params and no output schema, more context is warranted.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, description adds meaning for most parameters (onlyWithAttachments, subjectContains, fromContains, folder, mailbox) but omits 'top' and uses vague 'prefers'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it lists recent Outlook emails, specifies scope (Inbox default), and mentions filtering by subject and sender. Distinct from sibling attachment tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use versus alternatives like list_email_attachments or read_email_attachment. Does not state prerequisites 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 full burden. It only says 'start' without explaining the device-code flow, user interaction required, or what the tool returns. This lacks transparency about the process and side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that directly states purpose without unnecessary words. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (initiating an authentication flow), the description is insufficient. It omits expected return values, required user action (e.g., entering device code), and how to proceed after the call. An output schema or more descriptive text would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters (100% coverage by schema). For zero-parameter tools, the baseline is 4. The description adds no param-level details, but no details are needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Start Microsoft 365 device-code login for the local Claude Desktop MCP process.' It uses a specific verb ('Start') and resource ('Microsoft 365 device-code login'), and distinguishes itself from siblings like 'auth_status' which likely checks authentication state.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates the tool's function (initiate device-code login) but provides no explicit guidance on when to use it versus alternatives like 'auth_status'. It does not mention prerequisites or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description only states 'check whether login has completed' without disclosing what 'completed' means, return format, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single 10-word sentence, front-loaded with verb and resource, no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Minimal for a simple tool; lacks explanation of what 'completed' means or what the output looks like. Without output schema, more detail would help.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters in schema; description adds context about 'local MCP process', which is useful. Baseline 4 for 0 params.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the verb 'Check whether' and the resource 'Microsoft 365 login for this local MCP process'. Distinguishes from siblings like begin_auth and health_check.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage after beginning auth or to check login state, but no explicit when-to-use or when-not-to-use compared to alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses supported file formats and automatic downscaling of large image previews, which are important behavioral traits. However, it omits details like auth requirements or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no extraneous words. The first sentence states the core purpose, the second adds key details (formats, size handling). Very efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema is provided, so the agent must infer the return format. The description does not explain what the tool returns (e.g., binary data, base64, parsed text) or how the IDs are used. Incomplete for a tool with no annotations and no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has three parameters with no descriptions. The description does not explain what messageId, attachmentId, or mailbox represent or how to obtain them, leaving the agent without guidance despite the schema having 0% coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (download and parse) and resource (Outlook attachment). It differentiates from sibling tools like list_email_attachments and list_recent_messages by specifying it downloads and parses a single attachment's content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for reading attachment content after listing attachments, but does not explicitly state when to use or when not to, nor does it mention alternatives or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description clearly conveys two behaviors: verifying server running and reporting auth state. Adequate for a simple tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with key info, no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Simple tool with no parameters or output schema; description covers essential purpose and behavior, though response format is unspecified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters, schema coverage 100%, baseline score of 4 applies; description adds no parameter info but none needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool verifies server running and reports auth state, with specific verb 'verify' and resource 'server and auth state'. Distinguishes from siblings like auth_status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage as a health check before other operations, but no explicit when-not or alternatives 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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