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Extract citations from text

extract_citations
Read-only

Extract legal citations from a block of text.

Pass in a paragraph, judgment extract, or skeleton argument and this
will identify all case citations, statute references, and CPR rules.
Returns each citation with its type and canonical ID for further lookup.

Args:
    text: Text containing legal citations

Input Schema

NameRequiredDescriptionDefault
textYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds genuine behavioral context beyond that: it names the three citation categories detected and describes the return payload ('each citation with its type and canonical ID'), which is what an agent needs to chain into a resolution call.

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 purpose, then scope, then return shape — a sensible order with no filler. The trailing Args block is somewhat redundant for a single self-evident parameter, which keeps it off a 5.

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?

An output schema exists, so return values need not be fully specified, yet the description still summarizes them usefully. Combined with the input examples and the stated citation categories, an agent has enough to invoke this correctly; only explicit sibling routing is missing.

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?

Only one parameter and schema coverage is 0%, so the description carries the burden. The Args block ('text: Text containing legal citations') largely restates the schema, but the earlier sentence about acceptable inputs (paragraph, judgment extract, skeleton argument) does add real semantic guidance about expected content and size.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Extract legal citations from a block of text') and enumerates exactly what counts as a citation: case citations, statute references, and CPR rules. The phrase 'canonical ID for further lookup' implicitly points downstream to resolve_citation, though no sibling is named outright.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives concrete input contexts ('a paragraph, judgment extract, or skeleton argument'), which tells the agent what to feed it, and 'for further lookup' hints that resolution is a separate step. However, it never explicitly says when to use extract_citations versus resolve_citation, resolve_citations_bulk, or autocomplete_citations.

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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