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fedlex.cite

Read-only

Cite an element as its canonical Fundstelle («Art. 7 Abs. 1 Bst. b LSV») from eli_version and eId: use to label a read place in the Belegkette. norm.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
eidYesThe place to label: an eId such as «art_7/para_1/lbl_b», «art_23_a» or «annex_3/lvl_u1».
langNoLabel language (de|fr|it|en|rm) — the manifestation read and the abbreviation used; default de.
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

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, and the description is consistent with that. It adds the canonical-citation output concept and the Belegkette use case, but does not disclose the exact return shape, language default behavior, or error cases. This is adequate but not rich.

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

Conciseness3/5

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

The main sentence is compact and front-loaded with purpose and an example. However, the trailing 'norm.' fragment is unclear and appears vestigial, which weakens the overall structure.

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

Completeness3/5

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

With no output schema, the description should define the return value more explicitly; it implies a canonical Fundstelle string via the example, which helps. It omits language handling and failure behavior, though the read-only annotation and complete parameter schema cover some ground.

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 repeats eli_version and eId as inputs but adds no syntax or behavioral detail beyond the schema; the lang parameter is only documented in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Cite'), a specific resource ('an element'), and the result ('canonical Fundstelle'), with the required inputs named. It is distinguishable from sibling tools like parse_reference by direction (structured inputs to canonical label), though it does not explicitly name that sibling.

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 a concrete when-to-use context: labeling a read place in the Belegkette. It does not state when not to use it or explicitly compare alternatives, so it falls short of full 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

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