Multiple tickers for one date. Every bar carries absolute open/high/low/close plus fractional change from that ticker's own daily open. $0.02/ticker, no limit.
| Name | Required | Description | Default |
|---|---|---|---|
| date | Yes | YYYY-MM-DD | |
| tickers | Yes | List of ticker symbols |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description details output content (OHLC + fractional change) and cost ($0.02/ticker, no limit). This adds significant value beyond basic schema, though error handling or rate limits are omitted.
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?
Two sentences, front-loaded with purpose, no wasted words. Every sentence adds distinct information.
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?
Output schema is absent, but the description partially explains return values. However, it lacks guidance on sibling tool differentiation and does not address error scenarios or limits beyond cost.
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 100% with descriptions for both parameters. The description does not add further syntax or meaning to the parameters themselves, but confirms the batch nature.
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 retrieves bars for multiple tickers on a single date, with specific output fields (OHLC and fractional change). This distinguishes it from siblings like get_bars which likely handle single tickers.
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 use for batch queries over multiple tickers for one date, but does not explicitly compare to alternatives like query_daily or get_bars. No when-not-to-use guidance is given.
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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Most tools have distinct purposes, but there is some overlap among bar-related tools (get_bars, query_minute_bars, query_range, query_daily). Descriptions are detailed enough to differentiate, but an agent might need to carefully choose the right bar tool.
Naming follows a consistent verb_noun pattern (get_*, query_*, scan_*). The only minor deviation is list_tickers instead of get_tickers, but it's still predictable.
15 tools is well-scoped for a market data API covering prices, fundamentals, filings, insiders, and screening. Each tool serves a clear purpose without being excessive.
The tool set covers a comprehensive range of market data needs: intraday/daily bars, fundamentals, SEC filings, insider transactions, company profiles, and screening. Notable missing features like options data are beyond the stated scope.