AI Law Tracker

List recent AI-law changes

list_recent_changes

Read-onlyIdempotent

Unified changelog: time-ordered inserts/updates across the whole dataset. Poll with since = the previous response meta.cursor. Paid feature (Developer+); the lookback window is clamped per tier. Data by AI Law Tracker (CC BY 4.0). Informational only — not legal advice.

Input Schema

TableJSON Schema

Name	Required	Description
`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.
`since`	No	ISO timestamp cursor — only changes observed after this (pass prior meta.cursor).
`entity`	No	Restrict to one dataset (default: both).
`offset`	No	Pagination offset.
`significant`	No	Drop internal metadata-only updates.
`jurisdiction`	No	Exact jurisdiction slug (e.g. california, us-federal, eu, canada). See list_jurisdictions.

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, etc. Description adds tier-based lookback clamping, paid restriction, and data attribution. No contradictions, but does not detail error handling or exact clamping behavior.

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 sentences, front-loaded with purpose and usage pattern, then essential caveats. Every sentence earns its place.

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 8 parameters and no output schema, description explains core intent and polling mechanism well. Lacks explicit response structure but implies cursor in meta. Sufficient for a list endpoint.

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 covers 100% of parameters with descriptions. Description reinforces 'since' usage and adds tier context for 'limit', but adds little beyond 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?

Description clearly states it's a unified changelog for time-ordered inserts/updates across the dataset, with polling using 'since' cursor. Distinguishes from siblings by focusing on change tracking rather than static lists.

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?

Explicitly describes polling pattern with 'since' parameter and mentions paid feature and tier clamping. Does not provide explicit when-not or alternatives to sibling tools, but usage context is clear.

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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