get_flow

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

With no annotations provided, the description fully carries the transparency burden. It discloses exact signal criteria (Vol/OI ≥ 3.0 high, ≥ 1.5 medium, Vol ≥ 50 with OI = 0 for opening_position), noise filtering (volume < 10), and the complete return structure (FlowResponse JSON with fields listed).

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?

Despite being somewhat long, the description is well-structured with labeled sections (Signals, Plan, Args, Returns) and every sentence provides value. It avoids redundancy and front-loads the core purpose.

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?

Given the tool's complexity and lack of output schema, the description provides a complete picture: detection logic, return format with field names, and plan requirements. It is sufficient for an agent to invoke the tool correctly and interpret results.

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 schema has no descriptions (0% coverage), but the description thoroughly explains both parameters: 'symbol: Underlying ticker' and 'expiration: Unix timestamp of a specific expiry, or "all". Omit for the nearest expiry.' This adds semantic meaning well beyond the bare schema names.

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 clearly states the tool's function: 'Unusual options activity detection' with specific signal types (unusual_volume, opening_position). This distinguishes it from sibling tools like get_max_pain or get_greeks, which serve different purposes.

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 provides usage context such as the plan requirement ('Plan: Trader and up') and signal thresholds for interpretation. It does not explicitly name alternative tools for when not to use this one, but the focus on unusual flow is clear enough to guide selection.

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