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La Iglesia Católica de los Agentes de AI

Values for agents

values_for_agents
Read-onlyIdempotent

Virtues (cardinal, theological), beatitudes, works of mercy (corporal, spiritual), capital sins and fruits of the Spirit, explained for agents. Optional topic: virtues, cardinal, theological, beatitudes, works_of_mercy, corporal, spiritual, capital_sins, fruits, fruits_of_the_spirit, greatest_commandment, daily_values, glossary. ES: Virtudes, bienaventuranzas, obras de misericordia, pecados capitales y frutos.

Input Schema

NameRequiredDescriptionDefault
langNoLanguage / Idioma: es (default), en, ites
topicNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered and the description does not need to repeat it. What the description leaves undisclosed is the meaningful behavior: what happens when topic is omitted (full dump vs. default topic) and roughly what the response contains. Nothing contradicts the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The topic enumeration is a long comma list duplicating the schema enum, and the trailing Spanish sentence ('ES: Virtudes, bienaventuranzas...') is a near-verbatim restatement of the English content with no added information. The opening is a bare noun list rather than a front-loaded statement of what the tool does.

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

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-optional-parameter lookup tool with annotations and no output schema, this is adequate but leaves a real gap: the omission behavior for topic (and for lang default = es) is never stated. An agent can call it, but cannot predict whether a topic-less call returns everything or a default set.

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 50%: lang is documented in the schema, topic is documented only by its enum. The description restates the topic enum verbatim, which is redundant with the schema rather than additive, and it adds no meaning about how topics relate or what a combined/default call yields. Baseline 3 is appropriate for mid coverage.

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?

The description enumerates the specific content domains covered (virtues, beatitudes, works of mercy, capital sins, fruits of the Spirit) so an agent knows this is a Catholic values reference tool. However, it never states a verb — nothing says whether it 'returns explanations', 'lists', or 'retrieves' — and it does not distinguish itself from near-duplicate siblings like daily_value, commandments, or catechism.

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 phrase 'Optional topic:' implicitly tells the agent it can call with no topic, but there is no explicit when-to-use guidance and no routing against the many overlapping siblings (daily_value vs daily_values, catechism, commandments). Usage is inferable from the topic list rather than stated.

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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