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by io.github.nalegaluorg

related_cases

Read-only

List SAOS cases related to one statutory provision.

    Use after identifying a relevant provision. A related-case link is not
    proof of a legal rule: inspect the judgment with get_case before
    asserting its holding. Deterministic lookup by act address
    (e.g. WDU19740240141) and article
    key. Returns case number, court, date, relevance score when available,
    and a SAOS link per case; scored cases sort first. Newer data also
    carries citation context per case: mentions (how many times the
    article appears in the judgment text), mention_match ("exact" =
    found with a matching act marker; "ambiguous" = bare mention,
    possibly another act's article — discount it), and context (snippet
    around the mention). mentions=0 or a missing context means the link
    comes from SAOS metadata but the text scan could not confirm it —
    treat relevance as unverified rather than assuming the case is on
    point. If count is zero, it means this local provision-to-case link
    dataset has no rows; it is not an exhaustive SAOS or case-law search.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
addressYes
article_keyYes
paragraph_keyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the readOnlyHint, the description details important behavioral caveats: related-case links may not be textually confirmed, uncertain relevance should be discounted, and mentions=0 or missing context means the link is unverified. It also explains how results are ordered by relevance score, which is valuable runtime behavior not stated in 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 main purpose is first sentence. All subsequent sentences carry substantive caveats or detail about result interpretation, and the warning about not treating counts as exhaustive is placed where it will not be missed. It is watchfull but not padded.

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?

The description covers about return fields, sorting, data provenance differences between richer and older data, how to interpret mention_match and mentions, and the local non-exhaustive boundary of the dataset. Given the output schema exists for return structure, the tool-level description leaves no meaningful calling or interpretation gap.

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?

With schema description coverage at 0%, the description compensates by explaining address and article_key with a concrete example (WDU19740240141) and by mentioning paragraph-level detail implicitly through 'one statutory provision.' It does not explicitly describe paragraph_key or limit, but limit is simple and paragraph_key is optional with a null default, so the important calling semantics are covered.

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 opens with a specific verb-resource statement: 'List SAOS cases related to one statutory provision.' It further defines the lookup as deterministic by act address and article key, which clearly separates it from siblings like get_case or research_cases. The scope is precise and actionable.

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?

It explicitly says 'Use after identifying a relevant provision,' giving a clear precondition. It also warns against treating related-case links as proof and directs the agent to inspect the judgment with get_case before asserting holdings. It further clarifies that a zero count is not an exhaustive SAOS or case-law search, providing both when-to-use and when-not-to-conclude guidance.

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

A4.6/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: search_law and get_article handle statutes, while related_cases, search_case_by_signature, get_case, and verify_quote handle case law, with health for diagnostics. No overlapping boundaries exist.

Naming Consistency4/5

Most tools follow a verb_noun pattern (get_article, get_case, search_law, search_case_by_signature, verify_quote), but related_cases and health deviate as noun phrases. The mix is minor and remains predictable.

Tool Count5/5

Seven tools is well-scoped for a legal research server, covering both statutory and case-law workflows without redundancy. Each tool earns its place.

Completeness5/5

The surface covers the full research lifecycle: searching and retrieving statutes, finding related cases, verifying citations, fetching case details, and validating quotes. No obvious gaps are present.

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