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Juriset

Get the rule on a date

get_rule_as_of
Read-onlyIdempotent

Get the rule that was (or will be) in effect on a date, in the same shape as get_rule. Example: {"rule_type": "minimum_wage", "jurisdiction": "us-wa", "as_of": "2025-06-30"}. Use it to see what applied when a past decision was made. A date before Juriset's coverage of that jurisdiction is answered with an error that says where coverage starts. Informational only, not legal advice. If the API key's plan does not include as-of queries the error says so.

Input Schema

NameRequiredDescriptionDefault
as_ofYesThe date, `YYYY-MM-DD`, past or future.
domainNoThe rule type's domain, e.g. `employment`. Optional: when omitted it is looked up from the rule type.
rule_typeYesRule type slug from list_rule_types, e.g. `minimum_wage`, `overtime`.
jurisdictionYesJurisdiction slug from list_jurisdictions, e.g. `us-wa` (Washington), `us` (US federal), `ca-ab` (Alberta).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world. The description adds real behavioral context beyond them: out-of-coverage dates return an error naming where coverage starts, plan-gated access returns a distinct error, and it carries an 'informational only, not legal advice' disclaimer plus the fact that future dates are valid.

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?

Front-loaded with the core behavior, then the example, then usage and edge cases. Dense and mostly waste-free; the legal disclaimer is slightly boilerplate but is arguably required for this domain.

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?

No output schema exists, but 'in the same shape as get_rule' plus the sibling tool list lets an agent infer the return structure. Error modes and an example call are covered. Only minor gap is not restating what happens with the optional domain parameter.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and each parameter is documented, so the baseline is 3. The description goes further with a full example call showing valid values for rule_type, jurisdiction, and as_of together, which conveys format and expected slug conventions better than the schema alone.

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?

States a specific verb (get), resource (the rule), and temporal scope (in effect on a date), plus the key differentiator 'in the same shape as get_rule'. That implicitly separates it from get_rule (current) and get_rule_history (change log) without ambiguity.

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?

Gives a concrete scenario: 'Use it to see what applied when a past decision was made.' It also covers the failure paths (pre-coverage dates, plan without as-of support). It stops short of explicitly routing to get_rule for the current rule, but the 'same shape as get_rule' framing makes that distinction inferable.

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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