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law.case-verify

Verify every US legal citation in a passage against the real CourtListener corpus to prevent hallucinations before quoting case law.

Instructions

Verify every US legal citation inside a passage of text against the real CourtListener corpus. Anti-hallucination check before quoting case law.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesA passage that may contain one or more case citations (e.g. "...as held in Marbury v. Madison, 5 U.S. 137 (1803)..."). The endpoint extracts and verifies each citation.
Behavior3/5

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

With no annotations provided, the description carries the full burden. It correctly states the core behavior (verifying citations against a real corpus) but fails to disclose limitations such as handling of invalid citations, rate limits, or potential latency. It adds useful context like 'anti-hallucination' but lacks completeness.

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 description is two sentences, front-loaded with the main purpose and context. Every sentence adds value without redundancy, making it highly efficient.

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?

For a simple tool with one parameter and no output schema, the description covers the input and purpose adequately but omits any indication of the output format or behavior (e.g., what happens when citations are valid or invalid). This leaves the agent guessing about the return value.

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?

The input schema covers 100% of the single parameter 'text' with a detailed description. The tool description reinforces the purpose but does not add new information about the parameter beyond what the schema already provides, meeting the baseline for high schema coverage.

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 states the tool verifies US legal citations against the CourtListener corpus, specifying the verb 'verify' and the resource 'US legal citations.' It distinguishes itself from sibling tools like law.case-search by focusing on verification rather than search.

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 provides clear context by framing it as an 'anti-hallucination check before quoting case law,' implying when to use it. However, it does not explicitly mention when not to use it or list alternatives, leaving room for improvement.

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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