List the 44 political data cubes of the Confederation (Abstimmungen, Wahlen, Bundesrat, Interessenbindungen): use to see what data exists. norm.
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | Label language (de|fr|it|en|rm); default de. The answer names the language it served, and «und» where a name carries no tag. | |
| limit | No | ||
| family | No | One of `fc`, `fch/apg`, `national-council-election`, `political-rights`; absent = all 44. | |
| offset | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already covers safety. The description adds that the tool lists a fixed set of 44 cubes, which is useful, but the trailing 'norm.' is cryptic and does not clearly disclose behavior to an agent. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the core action. The only flaw is the unexplained 'norm.', which adds noise without conveying useful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only list tool with no required parameters, the description covers the primary purpose. However, limit/offset behavior and the meaning of 'norm.' are left undefined, so an agent may not fully understand the tool's edge behavior from this description alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50%: lang and family are documented in the schema, but limit and offset are not, and the tool description does not compensate for them. It adds no meaning to any parameter, leaving half the parameter surface under-described.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'List the 44 political data cubes of the Confederation', and names concrete categories. This clearly distinguishes it from siblings like lindas.observations or lindas.describe_cube, which act on cubes rather than enumerate them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'use to see what data exists' gives a clear usage context. However, it does not explicitly mention alternatives or when-not-to-use it, so it stops short of full routing guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.