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Aethis-ai

aethis-mcp

Official
by Aethis-ai

aethis_rulebook_schema

Read-only

Retrieve a rulebook's composition and aggregated input fields to know which field_values to supply for decisions or inspect how rulesets are wired.

Instructions

Get the composition + aggregated input fields for a rulebook. Returns the outcome_logic Expr AST (how the bridged rulesets compose, e.g. A AND (B OR C)), the list of bridged rulesets (ruleset_name, ruleset_id, slug, status), and the union of all required input fields. Use this BEFORE aethis_decide on a rulebook_id to know what field_values to supply, or to inspect how a rulebook is wired. Pass a rulebook slug (e.g. aethis/uk-fsm) or opaque id (rb_*).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rulebook_idYesThe slug (e.g. `aethis/uk-fsm`) or opaque id (`rb_*`) of the rulebook

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.22.0

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered by structured data. The description adds return-structure detail but discloses nothing behavioral beyond the annotations (no auth requirements, rate limits, or error behavior), so a baseline 3 is appropriate.

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?

Three well-ordered sentences: purpose first, return contents second, usage and parameter format third. Appropriately sized and front-loaded, with only minor redundancy in the third sentence where the slug/id format restates the schema.

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

Completeness5/5

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

There is no output schema, so the description carries the full burden of explaining return values and does so thoroughly (AST expression, ruleset fields, union of required inputs). Combined with complete parameter documentation, an agent has everything needed to call and interpret the 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%, so the single rulebook_id parameter is already fully documented with the same slug/opaque-id examples the description repeats. The description adds no format or semantics beyond what the schema provides, so the baseline 3 holds.

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 and resource (get the composition + aggregated input fields for a rulebook) and enumerates exactly what is returned (outcome_logic AST, bridged rulesets list, union of required fields), which helps separate it from siblings like aethis_list_rulebooks or aethis_schema. Sibling differentiation is present but indirect rather than explicit.

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?

Gives a clear condition and names an alternative: 'Use this BEFORE aethis_decide on a rulebook_id to know what field_values to supply,' plus a secondary use 'to inspect how a rulebook is wired.' No explicit when-not guidance, but the intended call context is unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.