get_timeseries

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

No annotations provided, but description fully covers behavior: hits /v1/data, returns chronological order (last element latest), and warns that next_release is a snapshot from last publication, not live. Describes data source and limitations.

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?

Well-structured with front-loaded main action, examples, and caveats. Slightly long but every sentence adds value. Concise for the amount of crucial context provided.

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 output schema exists (not shown but present), description doesn't need return format. Covers use case, usage context, parameter semantics, caveats, and alternatives. Complete for a single-param tool with good annotations (or lack thereof).

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?

Only one parameter 'uri' with 0% schema coverage, but description explains what the URI is, provides examples like '/economy/.../l55o/mm23', and tells how to find them via CDID and dataset. Adds significant meaning beyond raw 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?

Explicitly states 'Get a PUBLISHED ONS time series by its website URI' and specifies it's for headline indicators like inflation rates, unemployment rate, GDP growth. Distinguishes from get_observations by highlighting dataset curation differences.

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 'PREFER THIS for headline indicators' and advises when to avoid alternatives, e.g., 'Prefer this over get_observations for latest X rate'. Also provides caveat about next_release and suggests using list_releases/get_release for live release dates.

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