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EdgarStack

by com.edgarstack
OverviewDiscussionsAdmin

Get end-of-day price history and return statistics

get_price_history
Read-onlyIdempotent

End-of-day stock price history for a US ticker from Tiingo (market data — SEC filings never include prices). Returns the series (open, high, low, close, split- and dividend-adjusted close, volume), dividends and splits in the range, and summary statistics on the adjusted close: total and annualized return, annualized volatility, maximum drawdown with its dates, and the range high and low. frequency: daily, weekly, monthly (default daily). Dates are YYYY-MM-DD; the default range is the last 12 months. Long daily ranges list only the latest 400 points (statistics still cover the full range) — use weekly or monthly for long periods. Not financial advice.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "ticker": "<ticker>"
    },
    "name": "get_price_history"
  }
}

Input Schema

NameRequiredDescriptionDefault
tickerYesUS ticker symbol, e.g. AAPL or BRK.B
endDateNoYYYY-MM-DD; default today
frequencyNodaily
startDateNoYYYY-MM-DD; default one year before endDate
includeSeriesNoSet false to return only the summary statistics

Schema Changelog

Changes observed during successful MCP inspections.

No schema history has been recorded yet.

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the read-only/idempotent annotations, the description discloses the full return payload (series fields, dividends, splits, return/volatility/drawdown statistics with dates) and a non-obvious truncation behavior: long daily ranges list only the latest 400 points while statistics still cover the full range. That is exactly the kind of behavior an agent cannot infer from annotations or schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

Contents, parameters, and caveats are ordered sensibly with no redundant restatement of the schema. The trailing "Not financial advice" is boilerplate that doesn't earn its place, a minor blemish on an otherwise dense and front-loaded description.

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

Completeness5/5

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 carries the burden of describing returns — and it does so precisely, enumerating series fields, corporate actions, and each summary statistic. Defaults, formats, and the truncation caveat are all covered, leaving nothing an agent needs in order to call it correctly.

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

Parameters4/5

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

Schema coverage is 80%, so the schema already documents most parameters. The description adds meaning the schema does not: the default range is the last 12 months, dates are YYYY-MM-DD, and the interaction between frequency and the 400-point listing cap, which affects how an agent should choose frequency.

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 names a specific verb and resource — end-of-day price history for a US ticker from Tiingo — and explicitly contrasts it with the sibling filing tools ("SEC filings never include prices"). An agent can distinguish this from get_filing_section or get_financials without further inspection.

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?

It gives actionable selection guidance for the frequency parameter ("use weekly or monthly for long periods") and clarifies the domain gap versus filing-based tools. It doesn't name a specific alternative price tool, but no sibling in the list provides prices, so the routing guidance is effectively complete for the available set.

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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