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by com.zipirapp
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Get lesson status

get_lesson
Read-only

Check a lesson's status (poll this after create_lesson and after approve_lesson)

Use whenever you need to know where a lesson stands: after creating it, while it renders, or before downloading. status is the machine state (queued | rendering | done | failed), phase is finer, needs_approval is true while the storyboard waits for a human, and next says which call to make next. Costs no minutes.

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": {
      "id": "<id>"
    },
    "name": "get_lesson"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesid

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description goes beyond that by disclosing the enumerated status values, the phase/needs_approval fields, and the cost model ('Costs no minutes'), which is real behavioral context an agent cannot get from structured fields. It stops short of describing the full response shape, keeping it at 4.

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 parenthetical poll instruction is front-loaded, followed by the when-to-use sentence and then field semantics. Every sentence carries distinct information; nothing is repeated from the title or schema.

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?

With no output schema, the description correctly compensates by explaining the key return fields (status enum, phase, needs_approval, next). Combined with the annotations, an agent has everything needed to call and interpret this tool.

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

Parameters3/5

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

Schema coverage is 100%, so the baseline is 3, but the actual schema description for `id` is only the word 'id', adding no meaning. The description contributes modestly by framing the id as a lesson identifier, but does not clarify the expected UUID format or error behavior for a bad id.

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?

States a specific verb and resource ('check a lesson's status') and immediately distinguishes it from sibling operations by naming create_lesson and approve_lesson as the calls it follows. An agent can identify this as the status-polling tool without inspecting the schema.

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

Usage Guidelines5/5

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

Explicitly names the trigger points: after create_lesson, after approve_lesson, while rendering, and before downloading. It also points to the `next` field as the mechanism for choosing the following call, so the agent is routed rather than left to infer.

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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