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Regulations.ai — Global AI Law Tracker

Recent regulation changes

recent_changes
Read-onlyIdempotent

What changed in AI regulation recently: records newly added, records whose status, dates or milestones changed (with the previous and new values), and dated milestones that fell due in the window, such as a law taking effect. Each result carries a change saying what happened and when. Rewritten analysis text is not counted as a change.

Input Schema

NameRequiredDescriptionDefault
daysNoLook-back window in days (default 30; free: up to 90, with an API key: up to 365)
limitNoMax results (free: up to 5; with an API key: up to 50)
jurisdictionNoOptional jurisdiction filter

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive/closed-world, so the safety profile is covered. The description adds genuine behavioral value beyond that: it enumerates the three change categories, notes that previous and new values accompany changes, and discloses the `change` field on each result plus the exclusion of rewritten analysis text.

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?

Three tight sentences, front-loaded with what counts as a change and followed by the result payload and the exclusion rule. No filler; each clause carries semantic weight.

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?

For a read-only list tool with full schema coverage and no output schema, the description adequately conveys what a result contains (a `change` with what and when). Pagination/ordering behavior is unstated, a minor gap given the `limit` parameter.

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 description coverage is 100%, so the schema already documents `days`, `limit`, and `jurisdiction` fully, including tier limits. The description mentions the look-back window concept but adds no syntax, format, or tier details beyond what the schema provides, so baseline 3 is appropriate.

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?

Names a specific resource (AI regulation records) and the exact operation: reporting what was newly added, what changed status/dates/milestones, and what fell due. The clause excluding rewritten analysis text sharpens the boundary, letting an agent distinguish this changelog tool from search_regulations or get_regulation without opening schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied rather than stated: an agent can infer this is the tool for 'what changed lately' while search/get are for querying current state, but no sibling is named and no when-not-to-use condition is given. The window concept hints at the temporal scope but does not explicitly route the agent.

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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