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

With no annotations, the description carries the full burden and does add real behavioral context: buckets are per published row and only Binance aggregates taker orders. These are non-obvious constraints an agent can't get from the schema. It doesn't cover return format, rate limits, or auth needs.

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?

Two dense sentences, front-loaded with the metric definition before the interpretive and venue caveats. Every clause carries information, though the prose is tight enough that parsing takes a moment.

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 2-parameter analytics tool with no annotations and no output schema, the bucket explanation is helpful, but the inputs (timeframe and symbol semantics) remain undocumented and a phantom exchange parameter is introduced. Adequate but with clear 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 description coverage is 0%, so the description must explain the two parameters, but it explains neither symbol nor minutes. Worse, it references an 'exchange=binance' argument that does not exist in the schema, which could mislead an agent about the call signature.

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?

States a specific metric and the exact bucket thresholds (retail <$10K, mid <$100K, large <$1M, whale >$1M), which tells an agent precisely what the tool returns. It does not name the closely related siblings (get_footprint, get_microstructure) it should be distinguished from, so differentiation is only implicit.

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?

Offers interpretive guidance ('whale-vs-retail divergence is the usual smart-money reading') and a comparison caveat ('compare buckets within one exchange rather than across venues'), but never states when to pick this over the related flow/microstructure tools. Usage is implied rather than explicit.

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