Generate a personalized study plan by analyzing weak points and exam question frequency, then schedule daily tasks and phases based on days remaining until the exam.
讀書計畫引擎（綁考試日的處方）：把「弱點×考點頻率」排成攻擊順序，依剩餘天數排出分相日程 （掃弱點→申論模擬→衝刺複習）＋今日該做什麼＋進度夠不夠的誠實判斷。days_remaining 請用 使用者的考試日期減今天算出。非及格保證，作答數據越多越準。
| Name | Required | Description | Default |
|---|---|---|---|
| daily | No | ||
| q_type | No | mcq | |
| target | No | ||
| days_remaining | Yes |
Changes observed during successful MCP inspections.
v0.6.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the disclosure burden. It honestly states limitations ('非及格保證') and data dependency ('作答數據越多越準'), and describes the scheduling behavior. It does not mention side effects or permission needs, but for a planning tool the key behavioral traits are covered.
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?
The description is dense but each clause earns its place: purpose, scheduling logic, output, parameter guidance, and caveat. It is front-loaded with the core purpose and does not repeat schema field names. Slightly long, but efficient for the information conveyed.
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?
Given no output schema and no annotations, the description gives enough context on output ('今日該做什麼＋進度夠不夠'), the main parameter, and the tool's behavior. What it lacks is explanation of the other three parameters and any return structure details, but the most essential context for calling the tool is present.
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 0%, so the description must compensate. It only explains days_remaining ('use exam date minus today'), leaving daily, q_type, and target entirely unexplained. This is a significant gap for an agent trying to select correct values.
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 clearly states it is a study plan engine that turns weaknesses × exam-point frequency into an attack order, creates a phased schedule, and tells what to do today plus progress judgment. This distinguishes it from siblings like get_progress or get_weak_topics, which only retrieve raw data.
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?
It explains how to compute days_remaining and sets expectations (not a pass guarantee, accuracy depends on answer data), but it does not explicitly say when to use this tool versus alternatives like get_weak_topics or practice_weak. The context is helpful but the when/not-when advice is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.