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fedlex.read_article

Read-only

Read one element (Artikel, Absatz, Anhang) of a dated consolidation by eId, e.g. art_6 or annex_u1/lvl_u1: use to quote a norm. norm.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
eidYesAkoma-Ntoso eId, e.g. «art_10a», or a path eId such as «art_2/para_1» or «annex_u1/lvl_u1».
langNoManifestation language (de|fr|it|en|rm); default de. Which languages a version carries as XML is the graph's answer — fedlex.list_expressions shows it before a read.
eli_versionYesDated consolidation: `<abstract-eli>/<YYYYMMDD>`.

Schema Changelog

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

  1. First observed

TDQS

A3.9/5.0
Behavior3/5

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

The readOnlyHint annotation already covers the safety profile. The description adds that the tool targets a single element of a dated consolidation, which is useful scoping. It does not mention return format or failure behavior, so it adds modest value beyond the annotation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded, quickly establishing the resource, addressing mechanism, and intended use. It loses a point for the awkward trailing 'norm. norm.' which reads like a typo and adds no value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite no output schema, the description covers what is read, how it is addressed, and why it is used, and the schema covers parameters completely. A note on the return representation would improve completeness, but nothing critical 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?

Schema description coverage is 100%, so the baseline is 3. The description's eid examples slightly reinforce the schema's own examples but add no new semantic information about parameter formats or relationships.

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 names a specific verb ('Read'), a specific resource ('one element (Artikel, Absatz, Anhang)'), and a specific addressing mechanism ('by eId'), with concrete examples like art_6 and annex_u1/lvl_u1. This clearly distinguishes it from whole-document reads such as fedlex.read_document.

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?

It gives an explicit intended use—'use to quote a norm'—which tells an agent when to invoke this tool. It does not provide exclusions or name alternatives, but the use case is clear enough.

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

A3.5/5.0
Disambiguation4/5

The tools are strongly namespaced and most have a clear 'use for' hint, so an agent can usually select correctly. A few near-neighbour pairs, such as fedlex.get_citations vs fedlex.get_references and facts.badge vs facts.latest, require careful reading but are still distinguishable.

Naming Consistency4/5

The <domain>.<snake_case_action> style is consistent and the fedlex/lindas families are predictable. However, several noun-style names such as meta.tools, lindas.observations, and facts.badge deviate from the verb_noun pattern, and the variety of get_/read_/list_/find_ verbs adds minor noise.

Tool Count2/5

With 52 tools, this is a very large MCP surface for one server; while each tool appears individually purposeful, the combined set is heavy for an agent to explore and select from. The gateway would be more manageable split into separate legal, data, and meta servers.

Completeness5/5

The Fedlex cluster covers the full legal-research workflow: search, version resolution, reading, comparison, citation checking, history tracing, consultations, and official publications. The LINDAS cluster covers cube discovery, schema inspection, filtering, and label resolution, and the directory/meta tools complete the capability-discovery loop. There are no obvious dead ends or critical missing operations.

Resources