Fintel Discovery — Financial Intelligence for AI Agents

Get Price History — Multiple Tickers

GetMultiTickerHistory

Read-onlyIdempotent

    Fetch OHLCV price history for multiple tickers in a single call.
    Returns a flattened table with columns like 'AAPL_Close', 'SPY_Volume', etc.

    Use this tool when:
    - You are comparing performance across multiple securities
    - You need correlated price data for a portfolio or basket of tickers
    - You want to compute relative performance or correlation matrices

    Pass symbols as a space-separated or comma-separated string:
    'AAPL MSFT GOOGL' or 'SPY,QQQ,IWM'.

    Source: Yahoo Finance via yfinance. No API key required.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`params`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already cover read-only, idempotent, and non-destructive behavior, and the description adds useful context: Yahoo Finance/yfinance as data source, no API key required, and a flattened per-ticker column format. It doesn't disclose rate limits or data-quality caveats, but those are minor for a read-only fetch.

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 compact, front-loaded with the core behavior, and organized with a use-case list plus a concrete input example. Every sentence adds information; the source note is the final, low-cost detail.

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?

The output schema handles return-value documentation, and the description covers the essential call pattern, use cases, and data source. It is slightly incomplete in not signaling how period/start/interval are expected to be used, but defaults and schema fill most of that gap.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must carry parameter guidance; it only explains the symbols format and does not cover the date range, period, or interval parameters. It repeats the symbol examples from the schema rather than adding semantics for the other nested params.

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 opening sentence names the action (Fetch), the resource (OHLCV price history), and the distinguishing scope (multiple tickers in a single call). It also tells what the response looks like (flattened table with per-ticker columns), so it cannot be confused with GetPriceHistory or other quote tools.

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 'Use this tool when' list gives concrete scenarios: cross-security comparison, portfolio/basket correlation, and relative performance. It doesn't explicitly state when not to use it or name alternatives such as GetPriceHistory, so it falls one step short of fully explicit routing.

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

A3.9/5.0

Disambiguation4/5

Most tools target a distinct resource and action, with clear separation between search and detail tools (e.g., SearchIAPDFirm vs GetIAPDFirmDetail, SearchBrokerCheck vs GetBrokerCheckDetail). A few pairs like SearchBrokerCheck and SearchBrokerCheckFirm could cause momentary confusion, but descriptions clarify individual vs firm scope.

Naming Consistency4/5

The dominant pattern is consistent: Search* for discovery, Get* for retrieval, with CamelCase throughout. Minor deviations like LookupTicker and MapInstrumentIds introduce different verbs, and SearchBrokerCheck does not explicitly signal 'individual' unlike SearchBrokerCheckFirm, but the overall convention remains predictable.

Tool Count2/5

With 32 tools, the surface is quite heavy and exceeds the 25+ threshold for 'too many.' While the financial intelligence domain is broad, several search/detail pairs and overlapping data-source tools could be consolidated to reduce cognitive load for agents.

Completeness4/5

The toolset covers major workflows well: 13F holdings, fund fee comparison, advisor due diligence, macro data, price history, options, and identifier mapping. Minor gaps exist, such as no standalone real-time quote tool, no news/sentiment data, and no direct CUSIP-to-company-name search, but these are workable around.

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