Compose structured course announcements from a topic, key points, and tone, then publish them or save them as drafts.
【AI 智能發公告】提供公告主旨、要點與語氣風格，AI 自動撰寫架構清晰、語氣得體（包含溫馨開場、要點清單、重要提醒、助教聯絡方式）之課程公告，並可選擇直接發布或存為草稿！
| Name | Required | Description | Default |
|---|---|---|---|
| tone | No | 語氣風格：正式嚴謹、溫暖親切、緊急重要、溫馨提醒 | warm |
| draft | No | 是否存為草稿（true 存草稿，false 立即發布） | |
| topic | Yes | 公告主旨（例如：期中考改期通知或實習分組名單出爐） | |
| topMost | No | 是否置頂標示為 HOT | |
| courseId | Yes | 課程 ID | |
| keyPoints | Yes | 公告欲傳達的關鍵要點清單 |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It usefully discloses the generated structure (warm opening, key-point list, important reminders, TA contact info) and that the result can be published immediately or saved as a draft — a real side effect. It does not state permission requirements, whether publishing is reversible, or what exactly is returned.
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?
A single front-loaded sentence with the AI-writing purpose first and the structural detail in a parenthetical. Dense but not padded; the bracketed tag and exclamation mark are cosmetic waste.
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 6-parameter mutation tool with no annotations and no output schema, the description covers the input story, the generated content shape and the publish-vs-draft outcome well. It leaves unclear what the tool returns when composing without publishing and says nothing about topMost behavior, which is a modest gap.
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 description coverage is 100%, so the schema already documents all six parameters including the tone enum. The description reinforces topic, key points, tone and the draft choice but adds nothing about topMost or courseId, so it earns the baseline rather than more.
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?
States a specific verb and resource: AI composes a course announcement from a topic, key points and tone, with optional publish or draft. An agent can tell it apart from create_bulletin because AI authoring is explicitly named, though the sibling is never called out by name.
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?
There is no explicit when-to-use or when-not-to-use guidance, and no reference to create_bulletin or copy_bulletin as alternatives. The only routing signal is implicit: you supply a topic, key points and tone, and the AI writes the body.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.