get_expiry_concentrationWhere the day's unusual premium sits along the expiry axis, in DTE buckets (0-7, 8-30, 31-90, 90+) with call/put splits. Heavy short-dated premium reads as event bets; heavy long-dated as positioning.
| Name | Required | Description | Default |
|---|---|---|---|
| date | No | Trading day, YYYY-MM-DD. Defaults to the latest available day. | |
| symbols | No | Comma-separated tickers, e.g. 'AAPL,NVDA,TSLA'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It explains the output structure (DTE buckets with splits) and adds interpretive value (event vs. positioning), which goes beyond a simple restatement. It does not mention limitations or edge cases, but the core behavior is well conveyed.
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 two sentences, front-loaded with the main purpose and followed by a concise interpretive heuristic. Every word earns its place, with no redundancy or filler.
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 specialized analytics tool with no output schema, the description conveys the core concept, bucket definitions, and suggests how to interpret results. It is sufficient for an expert user, though it leaves some ambiguity about the exact output format (e.g., percentage vs. count).
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 100%, so the parameters (date and symbols) are already documented. The description adds context about the tool's analytical focus but does not provide additional parameter-level meaning beyond what the schema offers. Baseline 3 is appropriate.
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 purpose: showing where the day's unusual premium sits along the expiry axis in DTE buckets with call/put splits. It uses a specific verb ("sits") and distinguishes it from sibling tools by focusing on expiry concentration rather than broader flow or IV metrics.
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 interpretative guidance for when to use this tool: heavy short-dated premium reads as event bets, heavy long-dated as positioning. This gives clear context on how to apply the output, though it does not explicitly name alternatives or state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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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.