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fedlex.search_text

Read-only

Find where a word occurs inside ONE consolidation (hits with eId and Artikel): use before read_article when the article is unknown. hint.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
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.
limitNoMax hits (default 20, at most 100); `total` counts beyond it.
queryYesWord or phrase; case-insensitive substring.
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

A4.3/5.0
Behavior4/5

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

The readOnlyHint annotation already covers the safety profile, lowering the bar. The description adds useful behavioral context by stating that hits contain eId and Artikel, which is essential for chaining into read_article. It does not discuss pagination or auth, but those are less critical given 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 commendably short and front-loaded with the core action and purpose, followed by a clear usage pointer. However, the trailing lone word 'hint.' is unexplained and introduces minor ambiguity, preventing a perfect score.

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?

For a read-only search tool with no output schema, the description covers what is searched, what hits contain, and the intended workflow (preceding read_article). Required inputs are documented in the schema, and the only omissions are minor details like pagination behavior, which the schema already addresses through the limit parameter.

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 all four parameters (lang, limit, query, eli_version) are fully documented in the schema. The tool description adds no parameter-level details beyond what the schema already provides, so it remains at the baseline.

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 verb ('Find where a word occurs') on a bounded resource ('inside ONE consolidation') and clarifies the output ('hits with eId and Artikel'). It also distinguishes this tool from sibling read_article by explicitly naming it, making the tool's role unmistakable.

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?

The description gives direct, actionable routing: 'use before read_article when the article is unknown.' The 'ONE consolidation' qualifier further signals that this tool is not for cross-law search, effectively excluding that alternative.

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