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Research a legal topic

research_pack
Read-only

Get a structured research pack on a legal area.

Returns the most-cited authorities (cases, statutes, procedural rules)
within the filtered scope, with legal test elements and usage examples
from other judgments. This is the richest tool -- use it for substantive
legal research on a topic.

Args:
    query: Optional text query to scope results
    domain: Legal domain slug (e.g. "landlord-tenant", "employment")
    court: Court code to focus on
    year_from: Earliest year to include
    year_to: Latest year to include
    disposition: Case outcome (allow, dismiss, grant, quash, refuse, remit)
    jurisdiction: "England & Wales", "Scotland", "United Kingdom"
    topic: Legal topic slugs — multi-select (e.g. ["unfair-dismissal", "discrimination"])
    target_court: Court code for the user's case — adds binding/persuasive status per authority
    top_authorities: How many top authorities per category (default 5)

Input Schema

NameRequiredDescriptionDefault
courtNo
queryNo
topicNo
domainNo
year_toNo
year_fromNo
dispositionNo
jurisdictionNo
target_courtNo
top_authoritiesNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false. The description adds useful behavioral context by explaining what the pack returns, how target_court adds binding/persuasive status, and how top_authorities controls result count. It does not discuss latency, limits, or result-size constraints, but the annotations reduce the burden.

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?

Front-loads purpose and return shape, then gives a compact argument list. For a 10-parameter tool, the length is appropriate and every section contributes useful information.

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 the 10 parameters and 0% schema coverage, the description is largely complete: it covers every parameter and explains the tool's output and purpose. It leaves out explicit sibling routing and some parameter formatting details, but the presence of an output schema reduces the need to explain return values further.

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 description coverage is 0%, so the description must carry the burden, and it does list all 10 parameters with meanings. It provides examples for domain, disposition, jurisdiction, and topic, and explains target_court's effect, though some entries like 'court: Court code to focus on' remain thinner than ideal.

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 ('Get a structured research pack on a legal area') and describes the return contents, including authorities, legal test elements, and usage examples. It distinguishes itself as the 'richest tool' for substantive research, though it does not name a sibling alternative.

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 clear usage context: use it for substantive legal research on a topic, and implies it is the comprehensive option by calling itself the richest tool. It does not explicitly state when not to use it or name alternatives such as search_cases or get_authority_detail.

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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