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by sf-shenfeng
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

get_lesson

Fetch a lesson's title, structure, and publish status from the current classroom. Compact by default; include full Markdown content when needed.

Instructions

读回一节课: 标题 / 结构 (概念+习题清单) / 发布状态 (published: published_at 非空=已发布, 空=草稿) / 正文。默认紧凑 (include_content 缺省 false): 只给结构与元数据 + content_chars 全文字数 + 开头节选, 不吐全文 — token 经济。要读全文 (批改前审教材 / resume-teaching 冷启动接课) 显式传 include_content: true, 返回体多一个 content_markdown 字段 (可能很长, 确认要再开)。只能读当前 pair 的课, 其他 pair (或不存在) 的 lesson_id 一律 NOT_FOUND。

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "lesson_id": "<lesson_id>"
    },
    "name": "get_lesson"
  }
}

Input Schema

NameRequiredDescriptionDefault
lesson_idYes必填; 要读回的 lesson id (lsn_ 前缀), 须属当前 pair
include_contentNo可选, 默认 false (紧凑: 结构+元数据+节选)。true = 附 content_markdown 全文 — 只在真要读课文时开。

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the default compact behavior, the optional full-content flag, the inclusion of content_chars and an excerpt in compact mode, the error behavior (NOT_FOUND for non-current pairs), and the potentially long content_markdown. This is far more transparent than typical tool descriptions.

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

Conciseness5/5

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

The description is a single, dense paragraph that front-loads the core purpose and then efficiently covers behavior, parameters, and constraints. Every sentence adds detail: token economy, error case, and pair restriction. There is no fluff or repetition.

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

Completeness5/5

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

Given only 2 parameters, no output schema, and no annotations, the description is remarkably complete. It explains the default response shape, the optional field, the error condition, and the intended use cases. An agent can decide whether to invoke the tool and with what arguments without needing additional context.

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

Parameters4/5

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

Schema coverage is 100% for both parameters, so the baseline is 3. The description adds significant value beyond the schema: it explains the default value of include_content (false), the token-economy rationale, specific use cases for true, and the constraint that lesson_id must belong to the current pair. This elevates the score above baseline.

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

Purpose5/5

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

The description opens with '读回一节课' (read back a lesson), specifying a clear verb and resource. It enumerates exactly what is returned (title, structure, publish status, body), and distinguishes itself from siblings like get_lesson_closure_state by focusing on the lesson's full content and metadata.

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

Usage Guidelines4/5

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

The description explicitly states when to use the default compact mode (token economy) and when to pass include_content=true, citing concrete use cases such as grading prep and resume-teaching cold start. It also clarifies the limitation that only the current pair's lessons are accessible. It does not name alternative tools for explicit comparison, but the guidance is clear enough for an agent to decide.

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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