AI Law Tracker

Get AI-law obligations

get_ai_obligations

Read-onlyIdempotent

The interpreted "what must I do" layer: who must do what, by when, or owe what penalty, for a jurisdiction and/or sector. Every obligation is grounded in a real law record + primary source (no LLM). Provide at least a jurisdiction or a sector. Paid feature (Pro+); lower tiers get a one-item preview with an upgrade hint. NOT legal advice.

Input Schema

TableJSON Schema

Name	Required	Description
`use`	No	Comma-separated AI uses: hiring, customer, content, analytics, product, other.
`sector`	No	A sector slug (see list_sectors), e.g. healthcare, finance, hr-recruiting.
`jurisdiction`	No	Exact jurisdiction slug (e.g. california, us-federal, eu, canada). See list_jurisdictions.
`decision_impact`	No	What the AI decides about people (escalates applicability).

TDQS

A4/5.0

Behavior4/5

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

The description adds useful behavioral context beyond the annotations: it discloses tier restrictions (Pro+ feature with preview for lower tiers) and includes a disclaimer that it is not legal advice. This provides important caveats for the agent's decision-making. No contradiction with annotations.

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 at three sentences, with the key purpose front-loaded. It avoids repetition. Minor verbosity in 'grounded in a real law record + primary source (no LLM)' is acceptable for clarity.

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

Completeness3/5

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

The description adequately explains what the tool does and its constraints, but lacks detail about the output format or structure, which is important since there is no output schema. It does not mention pagination or limits, which could be relevant given openWorldHint=true.

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 add significant parameter-level semantics. The only additional guidance is 'Provide at least a jurisdiction or a sector,' which is a usage rule rather than parameter semantics. 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?

The description clearly defines the tool as providing an interpretation of 'what must I do' regarding AI law obligations, including who, when, and penalties. It distinguishes itself from siblings like get_ai_deadlines and get_ai_penalties by being the broader obligation layer. It also emphasizes grounding in real law records, not LLM output.

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 states that at least a jurisdiction or sector must be provided, and that it's a paid feature with a preview for lower tiers. It also includes a 'NOT legal advice' disclaimer. However, it does not explicitly say when to use this tool over specific alternatives like get_ai_deadlines or get_ai_penalties, though the sibling list implies the distinctions.

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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