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Ifá Wisdom — biblioteca de Ifá e Orixás

Glossário yoruba

get_glossary
Read-onlyIdempotent

O glossário do site (mais de 70 termos: Odu, Aché, ebó, babalawo, patakí…), com as variantes de grafia do Candomblé, da Santería e da Nigéria. Sem term devolve tudo, por seção; com term devolve só os verbetes que casam.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
termNo
localeNoIdioma da resposta: pt-BR (base), en, es.pt-BR

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / locale / description
      Previous value: -"Idioma da resposta: pt-BR (base), en, es, de."New value: +"Idioma da resposta: pt-BR (base), en, es."
    • changedInput schema / properties / locale / enum
      Previous value: -[
      -  "pt-BR",
      -  "en",
      -  "es",
      -  "de"
      -]New value: +[
      +  "pt-BR",
      +  "en",
      +  "es"
      +]
  2. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is covered. The description adds real behavioral detail beyond that: the unfiltered call returns the whole glossary organized by section, while a `term` call returns only matching verbets.

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?

Two sentences, zero filler: the first front-loads what the glossary is and its scope, the second front-loads the `term`-present vs `term`-absent behavior. The example terms earn their place by conveying entry type and script variants.

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 and four annotations, the return-shape question (all sections vs. matching entries) is the one thing that most needed covering, and the description covers it. Minor gap: no note on response language interplay between `locale` and the multilingual spelling variants mentioned.

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?

Schema coverage is only 50% (`term` has no schema description), and the description compensates by defining exactly what `term` does and what its absence means, which is the key semantic an agent needs. It adds nothing for `locale`, but that parameter is self-documented via its enum and schema description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource: it is the site's Yoruba glossary, and it even enumerates the kind of entries (Odu, Aché, ebó, babalawo, patakí) and coverage (>70 terms). The resource is clearly distinct from siblings like get_article, get_odu and get_orixa, though it never explicitly contrasts itself with them.

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

Usage Guidelines3/5

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

The description explains the two operating modes — omit `term` to get everything section by section, pass `term` to get only matching entries — which is genuine usage guidance for selecting behavior. However, it gives no guidance on when to prefer this tool over search_library or the individual get_orixa/get_odu 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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