Search Outlook emails by keyword across subject, body, and sender using KQL, returning metadata for matching results.
按关键词搜索邮件（Microsoft Graph KQL，可搜主题、正文、发件人）。只返回元数据。
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | 返回条数，默认 15 | |
| query | Yes | 搜索关键词，例如 项目名称 或 发件人邮箱 |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already carry readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds genuinely useful context beyond annotations: it states the Microsoft Graph KQL query syntax and explicitly declares that only metadata is returned (no body content). These are valuable behavioral disclosures.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, front-loaded with the core purpose ('按关键词搜索邮件'), followed by the syntax and return-behavior caveat. Zero waste; every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter read tool with annotations covering the safety profile and a fully documented schema, the description covers the essentials: search scope, query syntax, and return behavior. It lacks detail on the exact metadata fields returned, but no output schema exists and the tool's simplicity keeps this minor.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so both query and limit are already documented, putting the baseline at 3. The description adds value beyond the schema by revealing the KQL syntax and the searchable fields (subject, body, sender) that constrain how query should be formed — information not present in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb (search) and resource (emails), and states the searchable fields (subject, body, sender). It distinguishes from siblings in spirit — get_email retrieves a single email, list_emails lists — but doesn't explicitly name the sibling it is not. Clear enough for an agent to separate it from the other tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (keyword search across subject/body/sender via Microsoft Graph KQL) but gives no explicit when-to-use vs alternatives, and no exclusions or guidance on choosing search_emails over list_emails. The context is implied, not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.