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get_court_opinions_citing_ag

Find North Dakota Supreme Court and Court of Appeals opinions that cite a given attorney general opinion. Enter an AG opinion number to retrieve citing court opinions, newest first.

Instructions

Find ND Supreme Court / Court of Appeals opinions that cite a given AG opinion.

The inbound direction of the AG citation graph. Court opinions cite AG opinions two ways — a docket cite (N.D. Op. Att'y Gen. 2003-L-11) or, more often historically, a date reference (Attorney General's opinion of February 18, 1975); both are captured (see ag_backlink). Returns the citing court opinions, newest first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum court opinions to return (default 20, max 100).
opinion_numberYesThe AG opinion number, e.g. "2015-O-13" or "75-18".

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries the behavioral disclosure burden and does well: it states that results are returned newest first, that both docket-style and date-style citations are captured, and that the relationship is inbound from court opinions to AG opinions. It does not mention read-only semantics or error/empty-result behavior, but the key behavioral traits are present.

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?

The main action is front-loaded in the first sentence, and the following two sentences provide valuable context about citation direction and citation formats with no filler. The 'see ag_backlink' note is slightly cryptic but does not undermine the overall efficient structure.

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 that the input schema fully documents both parameters and an output schema exists, the description supplies the remaining essential context: the graph direction, the specific opinion types involved, the citation forms handled, and the sort order. It is nearly complete, though it could have briefly named the reverse-direction sibling for even clearer routing.

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%, and both parameters already have clear descriptions in the schema, including the default and max for 'limit' and an example format for 'opinion_number'. The tool description adds no additional parameter-level detail, so the baseline of 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 uses a specific verb ('Find') and names the exact resource: ND Supreme Court / Court of Appeals opinions that cite an AG opinion. It also clarifies the graph direction as 'inbound,' which distinguishes it from reverse-direction siblings such as get_ag_opinions_citing.

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 clearly implies when to use the tool: when you need court opinions that cite a specific AG opinion. It gives useful context about the 'inbound direction' and the two citation styles, but it does not explicitly name alternatives or state when not to use this tool.

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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