AI Law Tracker

Search AI laws

search_ai_laws

Read-onlyIdempotent

Full-text search over the audited AI-regulation dataset (US state + federal, EU, global) by title and summary. Returns matching law records with jurisdiction, status, and the official source URL. Data by AI Law Tracker (CC BY 4.0). Informational only — not legal advice.

Input Schema

TableJSON Schema

Name	Required	Description
`q`	Yes	Search text (required), e.g. "facial recognition" or "hiring".
`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

A4.3/5.0

Behavior5/5

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

Annotations already indicate safe read-only behavior. The description adds detail: full-text search over a specific dataset, fields returned, data source, and disclaimer. No contradictions.

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?

The description is concise (four sentences) and front-loaded. Each sentence adds value, though it could be slightly more compact. No wasted words.

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

Completeness4/5

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

Given 10 parameters and no output schema, the description adequately explains the tool's purpose and return fields. It could mention pagination or rate limits explicitly, but the parameter descriptions cover limits.

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%, so the description does not need to repeat parameter details. The description provides context on search scope but adds limited new meaning beyond the 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 clearly states it is a full-text search over an AI-regulation dataset, specifies the scope (US state+federal, EU, global), and what is returned (law records with jurisdiction, status, URL). This distinguishes it from siblings like list_ai_laws which likely lists without search.

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?

The description explains when to use (full-text search) but does not explicitly differentiate from alternatives like list_ai_laws or provide 'when not to use' guidance. However, the verb 'search' and scope imply the usage context.

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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