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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds genuinely new behavioral context in 'Free, no quota' (cost/quota profile) and enumerates the kinds of attributes a definition contains (units, thresholds, dating, history depth). However, with no output schema, the shape of the returned definition remains vague and the enumeration is syntactic clutter rather than a clear contract.

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?

It is a single sentence, which is efficient in length, but the nested colon-list is hard to parse and forces the reader to disambiguate examples from returned attributes. The core purpose would be clearer with the field-definition statement stated first and the examples clearly separated.

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?

There is no output schema, so the description must carry the burden of explaining return content; it lists attributes (columns, unit, label thresholds, dating, tool, timeframes, history depth) but without structure or confirmation of which are always present. For a low-complexity, one-parameter introspection tool this is roughly adequate, but the ambiguity leaves gaps.

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 100% and the single parameter 'fields' is already documented as an array of field names, so baseline would be 3. The description goes beyond the schema by giving concrete example field names (liquidations_24h, oi_usd, cumulative_net_volume, ranking, context), which helps an agent construct valid input values.

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 phrase 'Full definition of data-tool fields' conveys a metadata/introspection purpose, and the mention of 'columns, unit of each column, label thresholds, dating, timeframes, history depth' hints at what a definition contains. But there is no verb (e.g. 'returns the definition of') and the run-on listing of 'output keys liquidations_24h, oi_usd, cumulative_net_volume, ranking, context' blurs whether those are inputs, outputs, or examples. An agent can guess this is a describe/lookup tool but must work to parse it.

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?

'Free, no quota' encourages calling it, which is a mild usage signal, but there is no statement of when to call this versus a data tool such as get_pair_data, nor whether it should precede interpreting a data response. No alternatives or exclusions are named.

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