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List AI laws

list_ai_laws
Read-onlyIdempotent

List AI-regulation records with filters (scope, jurisdiction, status, in_force, updated_since, keyword q), sorting and pagination. Use this to browse laws for a place; use search_ai_laws for free-text search. Data by AI Law Tracker (CC BY 4.0). Informational only — not legal advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoSubstring search over title + summary.
sortNoSort field (default updated_at).
limitNoPage size (max 100; free/anon are capped lower).
orderNoSort direction (default desc).
scopeNoOne of: state, federal, eu, global.
offsetNoPagination offset.
statusNoCase-insensitive substring match on status.
in_forceNoFilter by the in_force flag.
jurisdictionNoExact jurisdiction slug (e.g. california, us-federal, eu, canada). See list_jurisdictions.
updated_sinceNoISO timestamp; only records updated at/after this.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover readOnlyHint, idempotentHint, openWorldHint, destructiveHint. Description adds data source (AI Law Tracker, CC BY 4.0) and disclaimer ('Informational only — not legal advice'), which are valuable behavioral traits beyond 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?

Two concise sentences. First sentence covers purpose and available filters. Second sentence provides usage guidance, data source, and disclaimer. No wasted words.

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?

Given 10 fully documented parameters, rich annotations, clear description of purpose and usage, and no output schema requirement typical for list operations, the description is complete and informative.

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 coverage is 100% with each parameter described in JSON Schema. Description lists filters but does not add meaning beyond what's already in the schema, meeting baseline expectation.

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?

Description clearly states the tool lists AI-regulation records with filters, sorting, and pagination. It uses specific verb 'List' and resource 'AI-regulation records', and explicitly distinguishes from sibling tool search_ai_laws.

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?

Provides explicit guidance on when to use this tool ('browse laws for a place') and when to use the alternative search_ai_laws ('free-text search'). No ambiguity.

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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