Historical year-series for a metric in one canton (e.g. sunshine back to 1884, migration to 1981, rent to 2010). metric = key from list_metrics with history: rent_mean, net_migration_per_1000, foreigner_pct, sunshine_hours, balance_per_capita, beds_per_1000, jobs. Optional from_year.
| Name | Required | Description | Default |
|---|---|---|---|
| canton | Yes | ||
| metric | Yes | ||
| from_year | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'historical year-series' and optional from_year but lacks details on data limits, caching, or performance characteristics.
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 a single concise sentence with parenthetical examples, front-loading the main purpose. The list of metrics is slightly verbose but informative.
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?
While most key aspects are covered (metric values, optional from_year), the description does not explain the canton parameter format or the return structure (e.g., array of year-value pairs), which would improve completeness.
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?
With 0% schema coverage, the description adds significant value by listing valid metric keys, explaining from_year is optional, and noting that metric must come from list_metrics with history.
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 it returns 'historical year-series for a metric in one canton' with specific examples of metrics, distinguishing it from sibling tools like compare_cantons or list_metrics.
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 for single-canton historical data but does not explicitly state when to use or avoid this tool versus alternatives like compare_cantons or rank_by_metric.
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.
Each tool has a clearly distinct purpose: consultation, tax calculation, canton comparison, relocation cost estimate, single-canton data, historical trends, metric listing, ranking, commune search, and upcoming votes. No overlap or ambiguity exists.
All tool names follow a consistent verb_noun snake_case pattern (e.g., list_metrics, search_commune, estimate_net_move). No mixing of conventions or erratic naming.
With 10 tools, the server is well-scoped for its domain (Swiss living index). Each tool provides necessary functionality without being overwhelming or too sparse.
The tool set covers core CRUD-like operations: search, retrieve, compare, rank, trend, and estimate. Minor gaps exist (e.g., no direct tool for detailed commune-level rent or job data), but the overall coverage is strong for the stated purpose.