germany-mcp-server

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

With no annotations provided, the description carries the full burden. It discloses that data comes from the Federal Statistical Office via Eurostat, which adds context about source and reliability. However, it lacks details on rate limits, authentication needs, error handling, or response format (e.g., time series vs. single values), leaving behavioral gaps for a data retrieval tool.

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 well-structured with a purpose statement, indicator list, data source note, and parameter details in a clear 'Args:' section. It is appropriately sized for a 2-parameter tool, though the indicator list is lengthy (7 items), which is necessary but slightly reduces conciseness. No wasted sentences.

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?

Given no annotations and no output schema, the description is incomplete. It covers parameters well and mentions the data source, but lacks details on return values (e.g., format, units, time ranges), error cases, or usage constraints. For a statistical data tool with 2 parameters, this leaves gaps in contextual understanding.

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 0%, so the description must compensate fully. It does so excellently: it explains both parameters ('indicator' and 'year'), lists all possible enum-like values for 'indicator' with clear meanings (e.g., 'bip' for nominal GDP in million EUR), and specifies the default behavior for 'year' (last 5 years if omitted). This adds substantial meaning beyond the bare schema.

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 clearly states the tool's purpose: 'Offizielle deutsche Statistikdaten von Destatis abrufen' (retrieve official German statistical data from Destatis). It specifies the verb 'abrufen' (retrieve) and the resource 'Statistikdaten' (statistical data), distinguishing it from sibling tools like weather or traffic tools by focusing on economic/population statistics.

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 description implies usage context by listing available indicators (e.g., population, GDP) and noting data sources, but it does not explicitly state when to use this tool versus alternatives like 'get_energy_prices' or 'strom_erzeugung'. No exclusions or prerequisites are mentioned, leaving usage guidance incomplete.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.