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lindas.resolve_label

Read-only

Resolve an IRI to its label in one language with a fallback (Kanton, Partei, Gremium, Interessenbindung): use to name a value. hint.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
iriYesAny IRI, of any host (canton, country, legal form, gender).
langNo

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?

The readOnlyHint annotation already covers safety; the description adds useful behavior by noting single-language resolution with fallback and limiting the label set to Kanton, Partei, Gremium, Interessenbindung. However, it does not explain the fallback order, output shape, or failure behavior, which is notable without an output schema.

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

Conciseness2/5

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

The core sentence is compact and front-loaded, but the trailing 'hint.' is a stray, unexplained fragment that adds noise rather than instruction. The colon-plus-fragments structure makes the definition feel unfinished.

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

Completeness2/5

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

For a moderately simple tool with no output schema, the description gives the main purpose but omits the language identifier format, fallback behavior, and return contract. It also leaves the parenthetical entity list's scope ambiguous relative to the schema's claim that the IRI can be any host.

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 iri parameter is well-documented in the schema, but lang has no schema description; the description's 'one language with a fallback' partially clarifies that lang is the target language and that a fallback occurs. It stops short of giving language codes or explaining the null case, so it only partially compensates for the schema's coverage gap.

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 precise operation—resolving an IRI to its label—and adds key qualifiers (one language, fallback, specific entity categories) that go beyond the tool name. This is enough to distinguish it from siblings like lindas.describe, which describe resources more broadly.

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?

'use to name a value' is an explicit intended-use instruction: call this when a display label for an IRI is needed. It does not state exclusions or name alternatives, so it falls short of a 5, but the guidance is clear and contextually appropriate.

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