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Glama

Lexiara

by org.lexiara

Article-level national implementations

find_national_implementations
Read-onlyIdempotent

National provisions implementing one EU provision, with method and confidence per link. DERIVED data, not published by any authority: treat links not marked method='human' as leads to verify, and say so when citing.

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
eIdYesProvision identifier: 'sec_4' (section 4), 'art_2__para_1' (article 2(1)), 'sch_9' (Schedule 9). Use search or history endpoints to discover eIds.
workYesELI of the EU instrument, e.g. the VAT Directive.
jurisdictionNoISO country filter, e.g. 'UK', 'FR', 'EU'.
minConfidenceNoDrop links below this confidence (0-1).

Schema Changelog

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

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the readOnly and idempotent annotations, the description discloses important behavioral traits: the data is derived and unauthoritative, links not marked method='human' are unverified leads, and users should say so when citing. It also discloses the API-key requirement and monthly graph allowance, which are not visible 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 description is two compact paragraphs with no filler. The core function and critical data-quality caveat are front-loaded, followed by access constraints. Every sentence earns its place.

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?

Despite having no output schema, the description explains what is returned: national provisions with method and confidence per link, and how to interpret those links. It also covers access constraints and the distinction between free legislative text and metered graph data, making it complete enough 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?

Schema description coverage is 100%, and the schema already documents all four parameters, including the meaning of jurisdiction, minConfidence, and examples for eId. The description adds no additional parameter-level semantics, so it remains at the baseline for high schema coverage.

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 a specific operation: find national provisions implementing one EU provision, including method and confidence per link. The 'DERIVED data, not published by any authority' framing clearly distinguishes this from official-source lookup tools among the sibling list, such as lookup_provision or search_legislation.

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?

The description makes the intended use clear: this tool is for finding national implementing provisions from a derived graph, and it warns that non-human links should be treated as leads to verify. However, it does not explicitly name sibling alternatives or state when not to use this tool, so it stops short of full when/when-not 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

A4.2/5.0
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