Use this when the user wants OHLCV candle history for a Hyperliquid perp market (for analysis or charting).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of candles | |
| symbol | Yes | Coin symbol, e.g. BTC | |
| interval | No | Candle interval | 1h |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the description does not need to restate those. It adds that the tool returns historical OHLCV data, but it does not disclose output shape, ordering, pagination, or any other behavioral details beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
This is a single, front-loaded sentence that clearly states the trigger condition and the domain of the tool. There is no redundant wording or unnecessary background information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only candle-history tool, the description, schema, and annotations together cover the essential selection and invocation information. Minor gaps are the lack of explicit sibling differentiation and no description of the return value shape, but those are not critical given the simple output implied by OHLCV.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameters (symbol, interval, limit) are already well documented structurally. The description adds no extra semantic detail beyond what the schema provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the resource and action: retrieving OHLCV candle history for a Hyperliquid perp market. This semantically distinguishes the tool from siblings like get_price and get_orderbook by specifying candle history and the charting/analysis use case.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly states when to use the tool: when the user wants OHLCV candle history. It does not mention when not to use it or name sibling alternatives, but the use-case framing provides clear contextual guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct resource or action, but get_markets and get_price overlap in the data they return (price, 24h change, volume, funding), differing mainly by all-markets vs single-coin scope. The descriptions are explicit enough that an agent should rarely misselect, though the boundary is slightly blurry.
All tool names follow a consistent verb_noun snake_case pattern: get_ for reads, plus clear action verbs like place_, preview_, cancel_, close_, and set_. There is no mixing of styles or vague generic verbs.
13 tools is well within the ideal range for a trading-focused server. Each tool covers a distinct part of the workflow without feeling bloated or redundant.
The tool surface covers the full trading lifecycle: market data, account/position/order/trade reads, order preview and placement, cancellation, position closing, and TP/SL management. No obvious dead-ends or missing core operations for the stated Hyperliquid perp trading purpose.