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Glama

Lexiara

by org.lexiara

Who names this act, provision by provision

work_mentions
Read-onlyIdempotent

The act-level overview: every provision of every instrument in this corpus that names the given act, grouped by citing instrument, with the article of the act each citation resolved to (targetEId, null where the citation is act-level — which is most of them, and is not a defect). Each instrument also carries adoptions: definitions it BORROWS from this act rather than writing, which is a different claim and is counted apart, never summed with the citations. Use related_works for the same question at instrument level, which is public. A row asserts that the provision NAMES this act, and nothing about whether it implements or corresponds to it.

Derived-graph data: requires an API key on a signed-in account. The free plan carries a monthly graph allowance; the legislative text itself is always free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
eliYesELI URI or official number of the instrument — a French code has only the latter.
limitNoMaximum citing provisions, default 500, cap 2000.

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?

Annotations already declare readOnly, idempotent, non-destructive, but the description adds substantial behavioral nuance: null `targetEId` is expected and not a defect, `adoptions` are counted separately from citations, and citations assert naming only, not implementation or correspondence. It also discloses API-key and quota behavior 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 dense but every sentence earns its place: core semantics, counterintuitive null behavior, separation of adoptions from citations, sibling routing, and access requirements. The most important information is front-loaded.

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?

With no output schema, the description compensates by explaining the shape and meaning of the response fields, including `targetEId` and `adoptions`. It also covers access control, quota implications, and the boundary of what the data asserts. Nothing essential is missing for an agent to invoke this 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?

Schema coverage is 100%, so the schema already documents both `eli` and `limit`. The description does not add much parameter-level detail, but it does illuminate the meaning of the result fields. Baseline 3 is appropriate because the schema carries the parameter burden.

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 exactly what the tool returns: every provision of every instrument that names a given act, grouped by citing instrument, with `targetEId` resolved to an article where possible. It also distinguishes itself from related_works, so an agent can tell the two apart without reading schemas.

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 to use related_works for the instrument-level version of the same question, and clarifies that the related_works view is public. It also flags that derived-graph data requires an API key and consumes a monthly allowance, giving the agent concrete selection and authorization context.

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