AI Law Tracker

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

Name	Required	Description
`q`	No	Substring search over title + summary.
`sort`	No	Sort field (default updated_at).
`limit`	No	Page size (max 100; free/anon are capped lower).
`order`	No	Sort direction (default desc).
`scope`	No	One of: state, federal, eu, global.
`offset`	No	Pagination offset.
`status`	No	Case-insensitive substring match on status.
`in_force`	No	Filter by the in_force flag.
`jurisdiction`	No	Exact jurisdiction slug (e.g. california, us-federal, eu, canada). See list_jurisdictions.
`updated_since`	No	ISO timestamp; only records updated at/after this.

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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TDQS

A3.8/5.0

Disambiguation1/5

Multiple tools are nearly interchangeable: assess_ai_compliance and generate_compliance_report both take a business profile and return risk score plus obligations, and get_sector_detail overlaps with get_ai_obligations/get_ai_penalties. Additionally, list_recent_changes and list_law_feed both describe dataset changes, while list_jurisdictions overlaps with list_countries and list_us_states. An agent cannot reliably pick the right tool without reading fine print.

Naming Consistency4/5

The set mostly follows a consistent snake_case verb_noun pattern (get_ai_law, list_sectors, search_court_opinions). Minor deviations exist: assess_ai_compliance and generate_compliance_report use different verb styles for near-identical actions, and list_ai_law_news is inconsistent with list_ai_laws. Overall the pattern is still predictable and readable.

Tool Count2/5

With 28 tools, the server exceeds the comfortable range and includes several redundant or overlapping endpoints that could be consolidated. The broad domain justifies a larger surface, but duplicates like assess_ai_compliance/generate_compliance_report and the three jurisdiction listers make the count feel inflated rather than well-scoped.

Completeness4/5

The tool surface covers the core read-only AI-law workflow well: search and retrieve laws, obligations, penalties, deadlines, sectors, jurisdictions, bills, court opinions, news, and change history. Minor gaps remain, such as no way to fetch a single obligation/penalty record by ID and no separate news-detail endpoint, but these are workable and not dead ends.

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