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RCO-A2A - Regulatory Compliance Objects

List rule sets

list_rule_sets
Read-onlyIdempotent

List the versioned rule sets in force and formerly in force for a jurisdiction: id, version, hash, effective dates, artifact URL. Never the regulation text.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jurisdictionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rule_setsYes
jurisdictionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • removedInput schema / additionalProperties
      Removed value: -false
    • removedOutput schema / additionalProperties
      Removed value: -false
    • removedOutput schema / properties / rule_sets / items / additionalProperties
      Removed value: -false
  2. First observed

TDQS

A4/5.0
Behavior4/5

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

The annotations already signal readOnly, idempotent, non-destructive behavior, so the remaining burden is small. The description adds that former versions are included ('formerly in force') and that regulation text is never returned, which are concrete behavioral constraints beyond 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.

Conciseness5/5

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

One front-loaded sentence states the resource, scope, output fields, and the key negative constraint without filler. Every clause earns its place, and the structure supports fast parsing by an agent.

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?

For a single-parameter list operation with a read-only annotation profile, the description is complete: it names the parameter's role, the output fields, the historical scope, and the explicit exclusion of regulation text. The presence of an output schema covers return-type details, so nothing needed to invoke the tool correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, but it only restates 'for a jurisdiction' — little more than the property name. It does not explain the meaning of the enum values (including 'apex'), how to choose one, or any format expectations, so an agent still has to infer the parameter semantics from the bare schema.

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?

The description names a specific verb and resource: 'List the versioned rule sets in force and formerly in force for a jurisdiction' and enumerates the returned fields (id, version, hash, effective dates, artifact URL). The explicit 'Never the regulation text' distinguishes this metadata-list tool from content-oriented siblings such as get_record and resolve_compliance.

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 makes the intended use clear — retrieving versioned rule-set metadata for a jurisdiction — and the negative constraint 'Never the regulation text' implies when not to use it. However, it does not explicitly name sibling tools or state conditions for choosing list_rule_sets over get_record, list_issuers, or resolve_compliance, leaving the routing partly to inference.

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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