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List AI Governance Units

list_governance
Read-onlyIdempotent

List all AI governance units (regulations, standards, frameworks, playbooks — EU AI Act, ISO 42001, NIST AI RMF, agentic checklist) with id, slug, category, name and summary. Use this to browse the regulations and standards; use search for an obligation or control.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
localeNoLanguage of the returned body. Default: en.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYes
resultsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful scope context about what is being listed, but does not add behavioral details beyond that, such as pagination, ordering, or locale effects. With annotations present, a 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.

Conciseness5/5

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

The description is two sentences with no wasted words. The first sentence front-loads the action, scope, and return fields; the second provides routing guidance. The parenthetical examples are informative rather than redundant.

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 simple, optional-parameter list tool with an output schema and comprehensive annotations, the description is complete. It tells the agent what is returned, what the tool is for, and when to pick an alternative. The output schema handles return structure, and annotations handle safety guarantees.

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?

The only parameter, locale, has 100% schema description coverage including an enum of valid languages and a default. The description does not need to repeat this. The baseline of 3 applies because the schema fully documents the parameter semantics.

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 all AI governance units', enumerates the categories and examples (regulations, standards, frameworks, playbooks, EU AI Act, ISO 42001), and specifies the returned fields. It differentiates from the sibling `search` tool by clarifying that browse is for regulations/standards while search is for an obligation or control.

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?

The description explicitly states when to use this tool: 'Use this to browse the regulations and standards'. It also names the alternative `search` and the condition for choosing it: 'use `search` for an obligation or control'. This gives clear routing guidance.

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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