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Price history (OHLCV)

get_price_history
Read-onlyIdempotent

Get daily OHLCV price history for a ticker: open/high/low/close/volume. Use period_days to control how far back (default 365, max 3650).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
barsNohow many recent sessions to return when no window is given (default 20, max 120)
tickerYesTicker symbol, e.g. 'SPY', 'GDX', 'AAPL'
to_dateNoend of the window to quote, YYYY-MM-DD
from_dateNostart of the window to quote, YYYY-MM-DD
period_daysNoNumber of days of history (default 365, max 3650)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerNo
currentNo
date_rangeNo
total_barsNo
instrument_idNo
recent_pricesNo
period_return_pctNo

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so safety is covered. The description adds context about daily OHLCV granularity and default/max for period_days, which is useful beyond annotations. No contradiction.

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?

Two sentences, front-loaded with the core purpose, and every word contributes. No fluff or redundant explanation.

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?

Given the straightforward nature of the tool, the presence of an output schema, and complete parameter descriptions, the description is sufficiently complete for an agent to invoke it correctly. It might clarify the precedence between bars and period_days, but that is minor.

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 description coverage is 100%, so baseline is 3. The description repeats period_days default and max from the schema but adds no new meaning for bars, from_date, or to_date. It does not compensate beyond 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 'Get daily OHLCV price history for a ticker' with specific content (open/high/low/close/volume), and this distinguishes it from sibling tools like technical indicators or sentiment data. Verb and resource are explicit.

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 gives clear context that this tool is for daily price history and provides a usage hint for the period_days parameter. However, it does not explicitly mention when to avoid this tool or name alternatives, stopping short of 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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TDQS

A4.2/5.0
Disambiguation5/5

Each tool maps to a distinct data category or function (prices, indicators, levels, sentiment, macro, crypto, intermarket, breadth, news, etc.). The few related tools are clearly separated by current vs. historical data, specific ratios vs. multi-lens overviews, or news lookup vs. news search.

Naming Consistency4/5

The majority of tools follow a consistent get_<noun> pattern with snake_case (e.g., get_price_history, get_technical_indicators). Two news tools use a public_ prefix instead, creating a minor but visible inconsistency.

Tool Count5/5

15 tools is within the ideal range for a market-data server and each tool covers a meaningful slice of the domain without redundancy. The count feels well-scoped for the server's purpose.

Completeness4/5

The tool surface is impressively broad, covering prices, indicators, sentiment, macro, crypto, intermarket analysis, news, and methodology. However, common data types like fundamentals (P/E, balance sheets) and options chains are absent, leaving a few potential user questions unanswered.

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