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paulieb89

UK Legal Research MCP Server

Parse OSCOLA Citations

citations_parse
Read-only

Parses free text to extract and classify OSCOLA citations: neutral citations, law reports, legislation, SIs, and retained EU law. Optionally disambiguates ambiguous references.

Instructions

Extract and classify all OSCOLA legal citations from free text.

Identifies: neutral citations ([2024] UKSC 12), law reports ([2024] 1 WLR 100), legislation sections (s.47 Companies Act 2006), SIs (SI 2018/1234), and retained EU law (Regulation (EU) 2016/679).

Ambiguous citations (e.g. bare [2024] EWHC without division) are optionally disambiguated via LLM sampling. Resolves citations to TNA / legislation.gov.uk URLs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYesCitationsParseInput with text (max 50,000 chars) and disambiguate flag.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
citationsYesAll successfully parsed citations (confidence >= 0.7)
ambiguousYesCitations with confidence < 0.7; may have been partially disambiguated via sampling
text_lengthYesCharacter length of the input text
parse_duration_msYesTime taken to parse, in milliseconds
Behavior4/5

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

Annotations already provide readOnlyHint=true and destructiveHint=false, indicating safe read operation. The description adds behavioral context: identifies specific citation types, handles ambiguous citations via LLM sampling, and resolves to URLs. No contradictions.

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 concise: three clear sentences. First sentence states main purpose, second lists citation types, third covers disambiguation. No redundant text.

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

Completeness5/5

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

Given complexity (parsing legal citations with disambiguation) and existence of output schema, the description covers input constraints (max 50k chars), supported citation types, and disambiguation behavior. It is complete enough without needing to describe return format.

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%, so baseline is 3. The description doesn't add significant additional meaning beyond the parameter descriptions in the schema; both already describe the text and disambiguate parameters adequately.

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 states 'Extract and classify all OSCOLA legal citations from free text' with specific verb 'extract and classify' and resource 'OSCOLA legal citations'. It lists distinct citation types (neutral citations, law reports, etc.) and mentions optional disambiguation, clearly differentiating it from sibling tools like 'citations_resolve' and 'citations_network'.

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 implies usage for extracting and classifying OSCOLA citations from free text, but does not explicitly state when to use this tool versus alternatives (e.g., citations_resolve for resolution). No when-not-to-use or prerequisites are provided.

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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