searchSearch official economic statistics by free text, e.g. 'inflation barbados' or 'government debt japan'. Returns result ids that can be passed to fetch. Designed for deep-research connectors; for richer control use get_indicator / get_series.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| results | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, openWorldHint, and idempotentHint. The description adds value by specifying that the tool returns 'result ids that can be passed to fetch,' giving insight into the output format. No contradictions with annotations.
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 concise—two sentences—with no filler words. It front-loads the purpose and examples, then adds usage guidance efficiently.
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 the single parameter and presence of an output schema, the description is complete: it explains the input, output (IDs), and tool context. No further information is necessary for correct use.
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 description coverage, the description fully compensates by explaining the 'query' parameter as free text with examples ('inflation barbados', 'government debt japan'). This adds meaning far beyond the bare schema specification.
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 verb ('Search'), the resource ('official economic statistics'), and the method ('by free text'). It provides concrete examples and distinguishes from sibling tools like get_indicator and get_series, making the purpose unambiguous.
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 explicitly states that the tool is 'designed for deep-research connectors' and advises to use get_indicator/get_series for richer control. It also notes that returned IDs can be passed to fetch, providing clear usage guidance and alternatives.
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.
Tools are organized into clear functional groups (retrieval, search, verification, conversion), and pairs like get_indicator/get_series and verify_stat/verify_claims have explicit usage distinctions. The only minor overlap is between fetch and get_series, but their descriptions clarify when to use each.
Most tool names follow a verb_noun snake_case pattern (get_indicator, verify_stat, compare_sources), with a few single-word or noun-style exceptions (fetch, search, country_snapshot). The overall convention is predictable and consistent.
12 tools is within the optimal range for a domain of this complexity, covering retrieval, search, comparison, verification, conversion, and source listing without unnecessary bloat.
The surface covers the full workflow: discover indicators (search_indicators), search data (search), fetch data (get_indicator, get_series, fetch, country_snapshot), compare sources (compare_sources), convert values (fx_convert, inflation_adjust), verify claims (verify_stat, verify_claims), and understand sources (list_sources). No critical gaps are apparent.