learning-mcp

start_topic

Begin or resume learning any topic, getting the current step's instruction. Tracks mastery per element for spaced retrieval practice.

Instructions

Begin learning a topic, or rejoin one already in progress.

Call this first, whenever the user wants to learn or study something. Returns the instruction for the current step and nothing about later ones.

Re-calling this for a topic already underway resumes it rather than starting over — mastery is tracked per element, so a second pass would split the record rather than double it.

Args: topic: What to learn, e.g. "kafka consumer groups" or "options pricing".

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": {
      "topic": "<topic>"
    },
    "name": "start_topic"
  }
}

Input Schema

Name	Required	Description	Default
`topic`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 5, 2026

TDQS

A4.5/5.0

Behavior4/5

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

The description discloses meaningful behavior beyond the basic purpose: it returns 'the instruction for the current step and nothing about later ones,' and it warns about mastery tracking: 'mastery is tracked per element, so a second pass would split the record rather than double it.' With no annotations, this provides valuable transparency about side effects and output scope.

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 concise and well-structured. It starts with a clear purpose, adds usage guidance, then behavioral notes, and ends with a neatly formatted Args section. Every sentence contributes value, and there is no filler.

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?

For a simple single-parameter tool with no annotations and no output schema, the description covers purpose, usage, resume behavior, and the return constraint. It does not detail the output format, but it does say the return is an instruction, which is adequate for an agent to proceed.

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

Parameters5/5

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

The schema provides no parameter description, but the description fills the gap with 'topic: What to learn, e.g. "kafka consumer groups" or "options pricing."' This gives both semantic meaning and concrete examples, fully compensating for the 0% schema coverage.

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 a clear verb phrase 'Begin learning a topic, or rejoin one already in progress,' which immediately states the tool's function. It also distinguishes from siblings by positioning itself as the entry point: 'Call this first, whenever the user wants to learn or study something.'

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?

It gives explicit when-to-use guidance: 'Call this first, whenever the user wants to learn or study something.' It also explains the resume case with 'Re-calling this for a topic already underway resumes it rather than starting over.' However, it does not explicitly name alternatives or exclusions, such as when to use the sibling 'resume' tool instead.

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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