Get real-time price data for one or more crypto futures symbols. Returns current price, 24h high/low, volume, and 24h price change percentage.
| Name | Required | Description | Default |
|---|---|---|---|
| symbols | Yes | List of symbols to get prices for, e.g. ["BTCUSDT", "ETHUSDT"] |
| Name | Required | Description | Default |
|---|---|---|---|
| data | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds that it returns real-time data including specific fields, which is useful but doesn't go much beyond annotations. It could mention rate limits or that data is for futures symbols, but the annotations carry the safety burden, so adds a bit of value for the return context.
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?
The description is two sentences, front-loaded with the purpose and specific data fields. Zero wasted words, all info is relevant and valuable.
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?
Given there's an output schema and good annotations, the description doesn't need to explain return values in detail. It explains the scope (real-time price data for futures symbols) and gives the key fields, which is sufficient for a simple read-only tool with one parameter. It's complete enough for the complexity.
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% and the parameter 'symbols' is well-described in the schema. The description does not add extra meaning about the symbols beyond what the schema provides—it just mentions 'one or more crypto futures symbols', which matches the schema. Baseline 3 is appropriate since the schema does the heavy lifting.
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?
Description clearly states the tool gets real-time price data for crypto futures symbols, with a specific list of returned data (current price, 24h high/low, volume, 24h change). It distinguishes from siblings like get_candles and get_technical_indicators, which have different scopes.
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 states the tool is for getting real-time price data for one or more symbols, which implies it's the go-to for current price snapshots. It doesn't explicitly mention when not to use it or name alternatives, but the sibling list and clear purpose provide adequate context. Lacks explicit exclusions like 'use get_candles for historical data'.
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.
Most tools are clearly distinct, targeting different data categories (market data, signals, traders, account). Some potential overlap exists between get_price, get_candles, and get_market_stats, but their descriptions clarify the specific use cases. Overall, an agent can differentiate them reliably.
All tools follow a consistent verb_noun pattern with the verb 'get' and a descriptive noun (e.g., get_candles, get_signals, get_trader_profile). This uniform naming makes it very predictable for an agent.
With 15 tools, the count is within the ideal range for a domain-specific server. Each tool serves a distinct purpose related to market data, signals, and trader analytics, and none feel redundant or extraneous.
The tool set covers core read operations for market data, signals, traders, and account info, which aligns with the apparent purpose of a data-provider server. Minor gaps include lack of write operations (e.g., placing trades) or historical signal details beyond individual IDs, but these are not critical for a data-oriented service.