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Language learning: Add material

language_add_material

Add a video or audio link to the caller's language learning. Preparing it (transcript + analysis) happens in the background and takes minutes; poll language_get_material for the status. NOT auto-approved: it fetches a third-party URL and spends an analysis call, so the caller confirms it. CONFIRMATION: this tool is PROPOSED, never performed directly. You get status='confirmation_required' with an action_id and a plan_token, and the write happens only after confirm_action.

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": {
      "url": "<url>"
    },
    "name": "language_add_material"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYes
languageNoLanguage being learnt, e.g. 'en'. Defaults to the caller's only profile.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Beyond readOnlyHint=false/destructiveHint=false, it discloses that preparation is asynchronous and takes minutes, that a third-party URL is fetched and an analysis call is spent, and that the call never writes directly but returns status='confirmation_required' with action_id and plan_token. That is exactly the extra context annotations cannot carry.

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?

Front-loaded with the purpose, then background behavior, then the confirmation contract; sentences are dense and purposeful. Mild redundancy between "NOT auto-approved... so the caller confirms it" and the CONFIRMATION paragraph restating that it is proposed and never performed directly.

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

Completeness4/5

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 explains what the caller receives (status, action_id, plan_token) and the full propose-then-confirm lifecycle. Gaps remain around url validity rules and behavior for duplicates or already-added media, but nothing essential to invoking it correctly is missing.

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?

Schema coverage is only 50%: the url parameter has no schema description, and the description says merely "a video or audio link" without stating accepted forms, providers, or whether playback pages vs. direct media URLs are valid. Only the language parameter is documented (in the schema), so the description does not compensate for the coverage gap.

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: "Add a video or audio link to the caller's language learning." It also names the counterpart tool for the follow-up step (language_get_material), so an agent can separate this from list/get material siblings without inspecting schemas.

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?

Gives explicit when-to-use (attach a video/audio link), what to do next (poll language_get_material for status), and the approval path (propose, then confirm_action). The alternative path is named, not just implied.

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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