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Lexiara

by org.lexiara

Where the law defines a phrase

define_term
Read-onlyIdempotent

The definition of a term of art, and the provision that gives it. Ask this BEFORE search_legislation whenever the question is what a phrase means ('durable medium', 'taxable person'): search returns provisions that USE a phrase, this returns the law that DEFINES it, verbatim. A term defined by several instruments returns several rows — the scope of each definition is the instrument carrying it, so check the work before applying one.

The definition text is always free. Only the adoption resolution (adopts, which act a borrowed definition comes from) is derived-graph data requiring an API key on a signed-in account.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
termYesThe phrase, e.g. 'durable medium'. Matched exactly (case-insensitive).
limitNoMaximum definitions, default 8.
jurisdictionNoISO country filter, e.g. 'UK', 'FR', 'EU'.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

The description adds meaningful behavioral context beyond the annotations: multiple instruments can return multiple rows, each definition's scope is tied to its instrument, and the adoption resolution requires API key authentication. It also clarifies that definition text is freely available, which is valuable operational knowledge. No contradiction with the readOnly/idempotent 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?

Every sentence earns its place: purpose, usage contrast, multi-row caveat, and authentication note are all packed densely without redundancy. The most important information is front-loaded, and the length is justified by the complexity of the tool's behavior.

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?

For a lookup tool with no output schema, the description covers what the tool returns, when to use it, how results behave across instruments, and the authentication requirement for certain data. Nothing essential for an agent to correctly select and invoke the tool 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?

The input schema already provides 100% coverage, including exact phrase matching, default limit, and jurisdiction filtering. The description adds useful examples and reinforces the exact-match behavior, but it does not substantially expand on parameter semantics beyond the schema.

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 identifies the tool's purpose: it returns the definition of a term of art and the provision that gives it. It actively differentiates itself from search_legislation, which returns provisions that use a phrase rather than define it. This is specific and unambiguous.

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 gives explicit guidance: use this tool before search_legislation whenever the question is what a phrase means. It names the alternative and explains the exact difference between the two, leaving no ambiguity about when to choose this 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

A4.2/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, and descriptions carefully separate overlapping areas such as definition lookup, cross-references, and transposition links. A few citation/graph tools (related_works, work_mentions, find_national_implementations, provision_context) could be confused at a glance, but their granularity and direction are explicitly differentiated.

Naming Consistency3/5

Naming follows a readable all-lowercase-snake_case style, but conventions are mixed: roughly half are imperative verb_object names (lookup_provision, search_legislation, list_topics) while the rest are bare noun-phrase view names (provision_context, recent_changes, work_mentions). The pattern is understandable but not uniform.

Tool Count4/5

At 18 tools, the set is slightly above the ideal 3-15 range, but each tool maps to a distinct research query or data product. The count is justified by the breadth of legal-research operations rather than redundancy.

Completeness5/5

The surface covers the domain thoroughly: search, provision lookup, definitions, multilingual terms, cross-references, amendment history, transposition links, topics, coverage, updates, and review workflows. The explicit read-only design means absent write operations are a deliberate boundary, not a gap.

Resources