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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds genuinely non-structured behavior: the mandatory citation/attribution string each result carries, and a scope caveat ('no index levels' in equity_positioning). It does not cover rate limits, error modes, or result formatting.

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?

Effective content density per table is high and the lead phrase is front-loaded, but the whole definition is a single ~400-word run-on paragraph with no line breaks or grouping. The length is largely justified by 15 undocumented enum values, yet the structure makes scanning for one table costly.

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?

For a 15-value enum selector with no output schema, the description covers what each table contains, which parameters apply where, and the citation obligation. Gaps are minor: return shape/pagination and confirmation that `layer` is required (not just suggested) for geography are not stated.

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 `name` enum values have no per-value descriptions in the schema, so the description is the only source of meaning for them, and it supplies that in detail. It also adds concrete examples for `layer` ('copper_prod, lithium_res, oil_prod') beyond the schema's one-line hint; only `country` is a near-verbatim restatement of the schema text.

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?

Opens with a specific verb+resource ('Platform tables') and then defines all 15 table identifiers with concrete content summaries (e.g. 'cot (CFTC long/short positioning)', 'stress (ECB CISS and OFR Financial Stress Index with percentiles)'). An agent can tell this apart from get_series/search_series, which return individual series rather than curated analytical tables.

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?

It implies usage through per-table data descriptions and states the scope of the country filter ('for the retail, labor and equity_markets tables') and the layer requirement for geography ('give layer, e.g. copper_prod'). However it never explicitly says when to pick this tool over get_series, search_series, or get_country_macro, so routing among siblings is left to inference.

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