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

With no annotations, the description carries the full burden and does well by disclosing cost, payment challenge flow, authentication methods, educational disclaimer, data fields, and hours lookback default. It omits output shape and pagination but covers the key operational behaviors.

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 front-loaded with cost and core capability, and each sentence earns its place: data scope, subscription comparison, payment instructions, authentication, and catalog pointer. It is longer than strictly minimal, but the monetization and access details justify the length.

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 paid API tool with no output schema and no annotations, the description provides enough to invoke it: data fields, payment mechanism, auth options, and hours lookback. However, it lacks limit semantics, response format details, and error/pagination behavior, leaving meaningful 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?

The description adds meaning for hours by calling it a lookback window with a default of 24, but it says nothing about limit's effect, units, or accepted ranges. With schema_description_coverage at 0%, the description should compensate more for both parameters.

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?

Description clearly identifies the tool as returning recent unusual options-flow signals with specific content: sweep clusters, large-premium prints, direction, strength, confidence, and size_bucket across the active equity universe. This scope distinguishes it from generic sibling signal tools.

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 implies usage context by framing this as a per-call alternative to options-flow subscriptions and directs users to get_catalog for browsing. However, it does not explicitly state when to prefer this over sibling signal tools such as get_signals, get_apex_signals, or get_anomalies.

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