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?
No annotations are provided, so the description carries the full burden. It discloses the output format (absolute OHLC and fractional change from the daily open) and pricing ($0.02/ticker, no limit), which is valuable context. It does not cover errors or permissions, but for a read-only batch query this is adequate and goes beyond the schema.
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 with no filler. It front-loads the core purpose, then adds output details, then pricing. Every sentence adds essential information, achieving maximum efficiency.
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?
With no output schema, the description's explanation of bar fields fills the gap by telling the user what to expect in the response. It also covers pricing and limits. It does not specify the exact response grouping or error behavior, but for a simple batch query, the description is sufficiently 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?
The schema already covers both parameters with descriptions, so the baseline is 3. The description adds meaning by clarifying there is no limit on the number of tickers, a constraint not present in the schema, and reinforces that the date is a single day. This is meaningful value beyond the schema.
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 states that the tool handles multiple tickers for a single date, which is a specific and distinct use case. This clearly differentiates it from sibling tools like query_range or query_daily that cover ranges or single tickers. The mention of OHLC and fractional change further specifies the output, making the purpose unambiguous.
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 usage when the user needs data for several symbols on one specific date, and the 'no limit' note suggests batch queries. It does not explicitly name alternatives or say when not to use it, but the 'one date' constraint provides clear contextual scoping against other query tools.
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.
Several tools overlap significantly: get_bars, query_minute_bars, query_range, and query_batch all provide intraday bar data, making it hard to distinguish when to use which. Additionally, get_brief and get_fundamentals overlap in fundamentals coverage. The descriptions do not clearly delineate boundaries between these tools.
The naming pattern is a mix of get_* and query_* prefixes, with list_ and scan_ as exceptions. While each individual name is readable, similar operations like get_bars and query_minute_bars use different verbs, making the overall convention inconsistent.
15 tools is a reasonable count for a comprehensive financial data server, covering market data, fundamentals, filings, insiders, and scanning. The count is not excessive, though the overlapping intraday bar tools suggest some redundancy that could be consolidated.
The tool surface is fairly complete for its domain, offering intraday and daily market data, fundamentals, SEC filings, insider transactions, company profiles, and market scanning. Minor gaps exist (e.g., no dedicated dividend/split tool), but these are not critical and can be worked around via existing tools like get_brief.