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get_bars

Resampled intraday bars at custom timeframes (3, 6, 9, 12, 15, 30, 60, 240 min) for one ticker. Every bar carries absolute open/high/low/close plus fractional change from the daily open, whatever the interval, and volume and transactions. $0.015 USDC per day.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNoMulti-day end date
dateNoTrading date YYYY-MM-DD
startNoMulti-day start date
tickerYesStock ticker (e.g. AAPL)
adjustedNoApply split adjustment (default false)
intervalYesBar interval in minutes: 3, 6, 9, 12, 15, 30, 60, or 240

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full transparency burden. It discloses the exact data fields returned (OHLC, fractional change from daily open, volume, transactions) and the cost per day, which is valuable. It does not cover pagination or the date vs. range distinction, but those are addressed in 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three concise sentences, each providing essential information: the tool's function, the structure of returned bars, and the pricing. It is front-loaded and contains no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description adequately explains the return value structure (OHLC plus additional fields) and the cost. It does not mention the 'adjusted' parameter's runtime behavior, but that is documented in the input schema. Overall, it is sufficiently complete for an agent to decide when to use it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds the constraint that it works for one ticker and repeats the allowed intervals, but it does not clarify the relationship between date, start, and end parameters. It provides minimal added meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that this tool returns resampled intraday bars at specific custom timeframes for a single ticker, listing the exact intervals. This distinguishes it from siblings like query_minute_bars or query_daily, 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.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for resampled intraday bars at custom intervals, providing clear context about what the tool does. However, it does not explicitly mention when to prefer this over alternatives like query_minute_bars, nor does it state any exclusions or prerequisites.

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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TDQS

B3/5.0
Disambiguation2/5

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.

Naming Consistency3/5

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.

Tool Count4/5

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.

Completeness4/5

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.

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