UK Business Tools - Ledgerhall

Get Case Citation Network

law_citations_network

Read-onlyIdempotent

USE THIS TOOL WHEN you have a judgment slug and want to map every citation it makes — cases cited, legislation referenced, SIs, retained EU law.

Fetches the judgment XML from TNA and parses all OSCOLA citations within. Returns citations grouped by type, deduplicated and sorted. AFTER calling, pass any individual citation through citations_resolve to confirm it resolves and to retrieve its canonical URL.

Useful for authority-network analysis (what did this judgment rely on?) and for surfacing the legislative landscape a case sits inside.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`case_uri`	Yes	TNA judgment URI slug, e.g. 'uksc/2024/12' or 'ewca/civ/2023/450'. Use the 'uri' field from case_law_search results — not the full URL. Do not include the 'https://caselaw.nationalarchives.gov.uk/' prefix.

Output Schema

TableJSON Schema

Name	Required	Description
`eu_refs`	No	Retained EU law references, e.g. 'Regulation (EU) 2016/679'
`si_refs`	No	Statutory Instrument references, e.g. 'SI 2018/1234'
`case_uri`	Yes	The judgment URI that was fetched and parsed
`law_report_refs`	No	Law report citations, e.g. '[2020] 1 WLR 100'
`total_citations`	Yes	Sum of all de-duplicated citations across every bucket
`legislation_refs`	No	Legislation section references, e.g. 's.47 Companies Act 2006'
`neutral_citations`	No	Neutral citations referenced, e.g. '[2020] UKSC 14'

TDQS

A4.7/5.0

Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds concrete behavioral details: it fetches the judgment XML from TNA, parses OSCOLA citations, and returns grouped, deduplicated, and sorted results. This significantly extends transparency beyond the annotations.

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 well-structured and concise: an upfront usage trigger, a brief process explanation, a follow-up instruction, and two high-level use cases. Every sentence earns its place, and the content is front-loaded with the most important information.

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 the tool has a single parameter, a detailed schema, an output schema, and helpful annotations, the description fully covers input, process, follow-up, and use cases. It leaves no significant gaps for an agent to select and invoke the tool correctly.

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 schema provides 100% coverage for the single parameter case_uri, including format, examples, and a prefix exclusion instruction. The description only uses the synonymous term 'judgment slug' and does not add new semantic information beyond the schema's rich definition, so the baseline score 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 clearly states the tool maps every citation a judgment makes, enumerating categories such as cases, legislation, SIs, and retained EU law. It is distinguished from siblings like law_citations_parse by focusing on the citation network extracted from a judgment's XML, with a specific verb+resource.

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

Usage Guidelines5/5

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

The description opens with 'USE THIS TOOL WHEN you have a judgment slug and want to map every citation,' which is an explicit usage condition. It also tells the agent to pass individual citations through citations_resolve afterward, providing clear follow-up guidance and alternative interaction via a sibling 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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TDQS

A4/5.0

Disambiguation4/5

Tools are well-grouped by domain prefixes (dd_, gov_, law_, prop_) with clear descriptions that differentiate them. However, there is minor overlap, e.g., dd_search could be used instead of individual searches, and dd_fetch versus dedicated profile tools might cause confusion.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern with domain-specific prefixes (dd_, gov_, law_, prop_). Names are descriptive and predictable, e.g., dd_charity_search, gov_govuk_search, law_bills_search_bills.

Tool Count4/5

70 tools is high but justified by the broad scope covering due diligence, government, legal, and property domains. Each domain has a reasonable number of tools (about 15-20 each). The count is on the upper end but still manageable.

Completeness5/5

The tool set is comprehensive across all domains: full CRUD for companies and charities, detailed legal research (cases, legislation, parliament, citations), property data (EPC, planning, price paid, rentals), and government information. No obvious gaps for the intended use cases.

Resources

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