get_key_series

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

Annotations already declare readOnlyHint and openWorldHint, so safety is covered. The description adds real behavioral context beyond that: 'no table IDs needed' (contrasting with the ID-based chain), that it returns the last `periods` observations, and that each series has specific statistical definitions (LFS seasonally adjusted, NIBOR + policy rate, 12-month inflation). It does not mention rate limits or exact output shape, but the output schema covers the latter.

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?

Front-loads the tool's role, then the series inventory, then usage and an example. The long enumeration earns its place because each entry resolves an otherwise opaque enum token; no sentence is filler.

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 an output schema exists, return values need not be explained; the description still covers scope, the alternative workflow it replaces, parameter meaning, and a concrete call example. Nothing needed to invoke it correctly is missing.

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 coverage is 50% — `series` is an undescribed enum, `periods` is documented. The description compensates by explaining what each enum value actually contains (cpi includes 12-month inflation; unemployment is LFS, seasonally adjusted), which is meaningfully more than the bare enum list, and confirms periods = last N observations.

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?

States a concrete verb+resource ('one-call shortcut' returning named Norwegian time series) and enumerates the six resolvable series, which no sibling tool offers. An agent can distinguish it from search_statistics/get_statistics/get_table_info purely from the description.

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?

Explicitly says to use it 'instead of the search/info/fetch chain' and gives representative natural-language queries ('what is inflation in Norway'), plus a worked example with series='cpi', periods=24. The routing decision is fully specified.

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