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Marketdata Candles

marketdata_candles
Read-onlyIdempotent

Get historical OHLCV candles for a stock symbol at a given resolution ("D" daily, "H" hourly, "5" for 5-minute, etc.). Provide a from/to date range. Example: marketdata_candles({ resolution: "D", symbol: "AAPL", from: "2026-01-01", to: "2026-06-30", _apiKey: "your-key" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoEnd date (YYYY-MM-DD), inclusive. Optional.
fromNoStart date (YYYY-MM-DD), inclusive. Optional.
symbolYesStock ticker symbol, e.g. "AAPL".
_apiKeyYesMarket Data App API token. Get one at https://www.marketdata.app/pricing/
countbackNoReturn this many candles counting back from `to` (mutually exclusive with `from`). Optional.
resolutionNoCandle resolution: "D" (daily), "W" (weekly), "M" (monthly), "H" (hourly), or a minute count like "1", "5", "15". Defaults to "D".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds no additional behavioral context (e.g., rate limits, data source specifics, response size) beyond what annotations provide. It is consistent with annotations, so no contradiction, but also no extra value.

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?

The description is compact: one sentence for purpose, one for instruction, and one example. The example is a bit verbose but front-loads the core concept. No wasted words; structure is clear and readable.

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

Completeness3/5

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

There is no output schema, and the description does not mention the return format or the countback alternative to from/to. However, the schema fully documents all parameters and the example covers the common use case. The tool is a simple read-only fetch, so this is adequate for correct invocation, but it could be more complete.

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 the baseline is 3. The description adds an example call and repeats resolution formats, but it does not add any new semantic meaning beyond the schema. The example is mildly helpful but not enough to raise the score.

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 states a specific verb ('Get'), resource ('historical OHLCV candles'), and qualifiers ('for a stock symbol at a given resolution'). This clearly distinguishes it from sibling tools like marketdata_stock_quote or marketdata_option_chain, even without naming them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

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

It gives explicit instruction to provide a from/to date range and includes a concrete example, but it does not mention the countback parameter as an alternative, nor does it explain when to choose this tool over sibling quote/option tools. The guidance is clear for the 'from/to' path but incomplete for the other mode and alternative selection.

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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