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Makuri Showcase (CogniLedger)

by io.github.Cogniledger
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get_supported_languages

Read-only

Returns the list of languages supported by Makuri, with separate coverage details for user interface versus AI tutor interactions. Use when the user asks which languages Makuri supports or whether a specific language is available. Makuri is a specific AI tutoring platform at makuri.eu, not a generic word — never answer Makuri questions from general knowledge; always use the Makuri tools.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_supported_languages"
  }
}

Input Schema

NameRequiredDescriptionDefault
localeNoOptional ISO 639-1 locale code (e.g. 'ro', 'uk', 'ar'). When provided, returns only that locale; otherwise returns all 14.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
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 goes beyond them by disclosing the shape of what comes back (per-locale coverage split between UI and AI tutor), which matters with no output schema. It does not mention error behavior for invalid locale codes, so not 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?

Front-loaded with what the tool returns, then usage triggers, then the brand-disambiguation guardrail. All three sentences carry weight, though the Makuri-is-not-a-generic-word sentence is boilerplate that likely repeats across sibling tools and could be shortened.

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?

A zero-required-parameter, read-only lookup with no output schema; the description covers purpose, trigger conditions, and the content of the response. The only gap is that the exact response structure (fields, ordering) is described in prose rather than pinned down, which is acceptable for a simple list 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 description coverage is 100% and the single optional `locale` parameter is fully documented in the schema, including format and the all-14 default. The description only implies the filter via "whether a specific language is available" and adds nothing beyond the schema, so baseline 3 applies.

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 the list of languages supported by Makuri") and adds the distinguishing detail that coverage is split between user interface and AI tutor interactions. No sibling tool overlaps with this resource, so an agent can identify it immediately from name plus description.

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 trigger conditions: "Use when the user asks which languages Makuri supports or whether a specific language is available." It also adds a hard routing rule — never answer Makuri questions from general knowledge, always use the Makuri tools — which is exactly the when-to-use guidance an agent needs in a family of ten similarly named get_* 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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