practice_weak

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral burden. It discloses the prioritization behavior (due-for-review and weakest points) and the hide_answer default, which are meaningful traits. It stops short of stating side-effect/read-only status, but nothing contradicts the schema.

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 compact sentence front-loads the core behavior and adds one parenthetical default. There is no filler or repetition beyond the short label '弱點練習', which the following clause immediately justifies.

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?

The core selection logic is clear and, since an output schema exists, return values are not a gap. However, with no annotations and several sibling practice tools, the lack of usage routing and undeclared n/q_type/subject semantics leaves the definition only minimally complete.

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 for parameter meaning. It only clarifies hide_answer's default; n, q_type, and subject semantics are left to inference from names and defaults, and q_type values are not explained.

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 states a specific function: generate practice questions while prioritizing today's due reviews and the weakest exam points. This distinguishes it from random_practice and practice_by_topic without naming them explicitly, though the verb is somewhat embedded in '出題'.

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?

Usage context is implied: use it when the user wants weak-spot/due-review drilling. It provides no explicit when-to-use or when-not-to-use guidance, nor does it point to alternatives such as random_practice or practice_by_topic, despite many sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.