get_symbol_flowEvery unusual contract on a single ticker, sorted by Vol/OI. Use when the question is about one specific stock's unusual options flow.
| Name | Required | Description | Default |
|---|---|---|---|
| date | No | Trading day, YYYY-MM-DD. Defaults to the latest available day. | |
| type | No | ||
| limit | No | ||
| symbol | Yes | Single ticker, e.g. 'TSLA'. | |
| date_to | No | Range end, YYYY-MM-DD inclusive. | |
| date_from | No | Range start, YYYY-MM-DD inclusive. | |
| min_voloi | No | ||
| min_premium | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses a behavioral trait by stating results are 'sorted by Vol/OI', but it does not clarify potential limits (e.g., 'limit' parameter overriding 'every'), return format, or how filters like min_voloi and min_premium affect results. This is adequate but not rich.
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 exceptionally concise and front-loaded: two sentences immediately state the core function and the primary use case. Every word adds value, with no fluff or repetition of schema details.
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 8 parameters and no output schema, the description is thin. It covers the primary purpose and when to use it, and the schema partially documents date/symbol parameters, but it leaves undefined the behavior of `limit`, `type`, `min_voloi`, and `min_premium` in terms of how they shape the returned 'every unusual contract' list.
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 minimal parameter meaning beyond the schema. It mentions 'single ticker' and 'Vol/OI', loosely linking to `symbol` and `min_voloi`, but does not explain the `type`, `limit`, `date_from`/`date_to`, or `min_premium` semantics. With 50% schema coverage, the description does not compensate for the undocumented 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?
The description clearly states it returns 'Every unusual contract on a single ticker, sorted by Vol/OI', which precisely identifies the tool's function and scope. It distinguishes itself from siblings by explicitly limiting to a 'single ticker' and focusing on unusual options flow.
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 gives an explicit usage scenario: 'Use when the question is about one specific stock's unusual options flow.' This provides clear context for when to invoke the tool, though it does not name alternatives or exclusion cases, preventing a 5.
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.