get_iv_rankIV rank and IV percentile per symbol against its rolling history (needs 20+ days). Pass a symbol for its IV-rank time series; omit it for a ranked snapshot (e.g. side=put&min_rank=0.8 finds elevated put IV).
| Name | Required | Description | Default |
|---|---|---|---|
| side | No | ||
| limit | No | ||
| symbol | No | Single ticker for its IV-rank series; omit for the snapshot. | |
| max_rank | No | ||
| min_rank | No | ||
| lookback_days | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden. It discloses the 20+ days history requirement, the two operational modes (time series vs snapshot), and the filtering semantics via example. It does not describe response format, pagination, or error behavior, but the core behaviors are covered.
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 exactly two sentences, front-loaded with the core function, and every word adds value. The example is compact and does not waste space.
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 tool with 6 optional parameters, no output schema, and no annotations, the description covers the primary modes but leaves some parameter purposes and return structure unexplained. The example gives one use case, but more detail on filtering and series behavior would make it more complete.
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 only 17% (only symbol has a description), so the description must compensate. It clarifies symbol (pass vs omit) and, via the example, side and min_rank. However, parameters like limit, max_rank, and lookback_days are not explained, leaving their semantics inferable but not explicit.
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 computes 'IV rank and IV percentile per symbol against its rolling history,' which is a specific, distinct function. It distinguishes from all sibling flow/OI tools by naming IV rank as the core resource, and the sentence structure is action-oriented.
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 explicit usage guidance: 'Pass a symbol for its IV-rank time series; omit it for a ranked snapshot' and gives an illustrative example with side=put&min_rank=0.8. However, it does not mention when to choose this tool over sibling alternatives (though no sibling is IV-related) or exclusion cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct analytical view (contract scan, per-symbol detail, history, sentiment, etc.), with clear boundaries. The only minor overlap is between get_symbol_flow and get_unusual_activity when filtering by a single symbol, but descriptions clarify the difference (single-symbol detail vs. broad scanner).
All tool names follow a consistent get_<object> pattern (e.g., get_expiry_concentration, get_oi_changes), with ping as the standard exception for liveness checks. The naming is predictable and uniform.
13 tools is well within the ideal range for a specialized data analytics server. Each tool covers a distinct query type and earns its place without redundancy.
The tool surface comprehensively covers the domain of unusual options flow discovery and analysis: data discovery, contract-level scans, per-symbol views, time series, sentiment, and market-wide aggregations. No obvious gaps or dead ends.