Search Bank of Canada data series

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 the core behavior—searching a catalogue and returning series names—and includes examples of typical queries. However, it does not detail search mechanics (e.g., fuzzy vs. exact matching, case sensitivity, or result ranking), but these are not critical for a simple search 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 two sentences long, front-loaded with the resource and scope, followed by the purpose of the search results. Every word earns its place without redundancy or unnecessary detail.

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?

The tool is simple, and the description covers the main purpose, input examples, and how the output is used (series names for get_observations). It does not describe the exact return format (e.g., array of strings vs. objects), but the stated purpose is sufficient for an agent to proceed, given the low complexity and absence of an output schema.

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?

The input schema already provides full documentation for both parameters, including defaults, constraints, and examples. The description adds little beyond schema, but it reinforces that the query is for keywords and that results are series names. With 100% schema coverage, the baseline of 3 is appropriate.

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 uses a specific verb ('Search') and resource ('Bank of Canada's catalogue of ~16,000 economic time series') with examples of content. It clearly distinguishes this tool from siblings like get_observations and latest_fx_rates by focusing on discovering series identifiers rather than retrieving data.

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 states that the tool returns series names for use with get_observations, which implies a workflow of searching first and then fetching observations. It does not explicitly exclude alternatives like latest_fx_rates or convert_currency, but the workflow context is clear and actionable.

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