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add_exercise

Add a new exercise to an existing lesson by specifying lesson ID, order, prompt, and reference answer.

Instructions

为 lesson 添加课后习题.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNo可选;自由标签的字符串数组(迁移 0039, 二审补的通道)。当前唯一约定值 "probe"——探针题标记(见 skill lesson-prep "探针与难度"),对学习者不展示、不告知。
orderYes
promptYes
lesson_idYes必须是已存在的 lesson id(server 会查存在性)
idempotency_keyNo可选。幂等键 (建议 uuid) —— 同一 key 重放此调用返回首次结果, 不重复写入. 网络重试/断线重连时带上同一个 key, 而不是猜"上次到底写没写".
agent_skill_usedNo
reference_answerYes
expected_conceptsNo可选;必须是字符串数组,且每个 id 都必须是已存在的 concept id(server 会查存在性)
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says "add exercises" and offers no information about side effects, idempotency (though the schema mentions idempotency_key), validation behavior, permissions, or whether existing exercises are affected. This is a significant gap for a write operation with an 8-parameter input.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clean sentence with no fluff or redundancy. It is front-loaded and immediately conveys the basic action, meeting the conciseness bar. It is admittedly sparse, but that issue is more directly punished in other dimensions.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given an 8-parameter tool with no output schema, no annotations, and no return-value description, a single sentence is far from complete. The agent has no information about expected outcomes, error handling, or how this tool interacts with lesson workflows, making it difficult to invoke correctly in a real scenario.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description does not mention any parameters, and schema description coverage is only 50% (4 of 8 parameters have descriptions). Key parameters like prompt, order, reference_answer, and agent_skill_used are left undocumented in both the schema and the description, leaving the agent without guidance on their format or required values.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description "为 lesson 添加课后习题" clearly states the action (add) and the resource (lesson), and references the concept of after-class exercises, which distinguishes it from sibling tools like add_flashcard or add_simulated_quiz. However, it is terse and does not explicitly name the object being created (e.g., an exercise entity with prompt/reference_answer), so it stops short of the most specific formulation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no guidance on when to use this tool versus alternatives, no mention of prerequisites (e.g., lesson must exist), and no exclusions. The agent is left to infer usage from the tool name and the minimal action phrase.

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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