List countries
list_countriesNational (global-scope) jurisdictions with AI-law record counts. Data by AI Law Tracker (CC BY 4.0). Informational only — not legal advice.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
list_countriesNational (global-scope) jurisdictions with AI-law record counts. Data by AI Law Tracker (CC BY 4.0). Informational only — not legal advice.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint, idempotentHint, etc. The description adds value with informational disclaimer and data source attribution, but does not disclose further behavioral traits like rate limits or response format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two sentences with no waste. First sentence is front-loaded with purpose, second adds context. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and no output schema, the description is fairly complete: it describes output (countries with record counts), data source, and disclaimer. It could mention sibling differentiation more explicitly, but still adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so baseline 4 applies. The description appropriately omits parameter details as there are none.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists national (global-scope) jurisdictions with AI-law record counts, using specific verb 'list' and resource. It distinguishes from siblings like list_jurisdictions and list_us_states by specifying 'national' and including record counts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for use (getting an overview of countries with AI laws) but lacks explicit when-to-use or when-not-to-use guidance, and does not mention alternatives among the many sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.