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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds useful context beyond them: the hard ticker allowlist and the api:read scope requirement. It does not disclose rate limits, payload size, or whether darkpool results are paginated.

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?

A single dense sentence front-loads the resource, then the kinds, then the auth requirement — no filler. It is slightly run-on, but every clause (tickers, kind semantics, scope) earns its place.

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 has no output schema, so the description should hint at what each kind returns structurally (fields, shape, time window conventions). It names the analytics but not the response form, and never mentions the darkpool date-window requirement that the schema only partially signals.

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 only 40% schema coverage, the description carries real weight: it maps each kind enum value to a concrete data product and constrains ticker to a fixed list. It leaves start/end (darkpool-required per schema) and limit entirely to the schema, so it does not fully compensate for the coverage gap.

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 names a specific resource (US equity options positioning) and enumerates exactly what each kind returns, plus the ticker universe. An agent can distinguish this from get_exposures or get_orderbook without opening the schema.

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 gives clear in-tool routing guidance: gex for gamma/charm/vanna, iv for IV rank/percentile/term structure, darkpool for dark-pool prints. It does not contrast this tool with adjacent siblings such as get_exposures or get_live_snapshot, but the kind-level disambiguation is strong.

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