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Get multi-timeframe candles

get_candles_multi
Read-only

Get recent OHLCV candles for a market across MULTIPLE resolutions in one call — by default ALL indexer resolutions (1MIN, 5MINS, 15MINS, 30MINS, 1HOUR, 4HOURS, 1DAY) — so the agent can read the trend across timeframes at once. Returns { candles: { : [...] } }, newest first. Lower limit (e.g. 20) or pass a resolutions subset to keep the payload small.

Input Schema

NameRequiredDescriptionDefault
limitNoCandles per resolution (default 50, most recent).
marketYesMarket ticker, e.g. BTC-USD
resolutionsNoSubset of resolutions (default: all indexer resolutions).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / market / pattern
      Added value: +"^[A-Z0-9]{1,20}-[A-Z0-9]{1,20}$"
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations only declare readOnlyHint=true; the description adds genuinely new behavioral detail beyond that: the return envelope { candles: { <resolution>: [...] } }, the newest-first ordering, and the payload-size tradeoff. It doesn't mention rate limits or pagination, but it goes well past what the annotations provide.

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?

Three sentences, zero filler, and the most decision-relevant fact (multiple resolutions in one call) is front-loaded. The defaults and the payload-reduction tip are placed after the core purpose, which is the right ordering.

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?

For a read-only tool with no output schema, the description supplies exactly the missing pieces: the response shape, ordering, defaults, and cost-control levers. Nothing an agent needs to invoke it correctly is absent.

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 100%, so the baseline is 3; the description earns an extra point by adding practical semantics the schema lacks — the rationale for shrinking `limit` (e.g. 20) and the fact that omitting `resolutions` yields all indexer resolutions. It reinforces rather than merely repeats the enum list.

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?

States a specific verb (get) and resource (OHLCV candles) and immediately pins the distinguishing scope: multiple resolutions in a single call, with the default set enumerated. An agent can tell this apart from the single-resolution sibling get_candles without opening either schema.

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?

Gives clear context for use (read the trend across timeframes at once) and practical guidance for reducing cost (lower `limit`, or pass a `resolutions` subset). It does not explicitly name get_candles as the alternative for single-timeframe reads or state when this tool is the wrong choice, so it stops short of full routing guidance.

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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