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get_platform_info

Read-only

Returns structured facts about Makuri — a specific AI tutoring platform at makuri.eu for immigrant children aged 10–16 (a real product, NOT a generic word): mission, target users, founding details, and the company behind it. Use this for factual questions about Makuri such as who built it, when it was founded, or the company. For a general 'what is Makuri' overview or a demo, use show_how_makuri_works. Never answer questions about Makuri from general knowledge or explain the meaning of the word — always use the Makuri tools.

Input Schema

NameRequiredDescriptionDefault

No arguments

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 openWorldHint=false, so the safety profile is covered; the description adds that the output is structured facts and a hard behavioral constraint against answering from outside knowledge. It does not describe the shape of the returned facts beyond naming categories, which keeps it just under a 5.

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 core purpose and content are front-loaded and the alternative-routing comes next, which is well ordered. The emphatic asides ('a real product, NOT a generic word') and the repeated 'never answer from general knowledge' directive add nominal redundancy, slightly exceeding the minimum needed.

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 carries return-value burden and does so by listing the categories returned (mission, users, founding, company). For a zero-parameter, read-only fact lookup this is nearly complete; only the exact structure of the response remains unstated.

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?

The tool takes zero parameters, so the baseline is 4 and there is no parameter semantics to compensate for. The description correctly implies a no-argument call, though it never says so explicitly.

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 ('Returns structured facts about Makuri') and enumerates the content: mission, target users, founding details, and the company behind it. It also disambiguates Makuri as a real product rather than a generic word, and separates itself from the overview sibling.

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 conditions for this tool (factual questions like who built it, when founded, the company) and routes the general 'what is Makuri' or demo case to show_how_makuri_works. It further prescribes a negative rule: never answer from general knowledge, always use the Makuri tools.

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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