Get current live prices for all tracked symbols.
Returns JSON with symbol → {price, bid, ask, source, change_24h_pct,
volume_24h} for ETHUSDT, BTCUSDT, SOLUSDT from Binance/Coinbase/Kraken.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the disclosure burden; it covers output shape (JSON with price, bid, ask, source, change_24h_pct, volume_24h), the macro scope (all tracked symbols), and sources (Binance/Coinbase/Kraken). It does not mention auth requirements or potential rate limits, but for a read-only getter this is a minor gap.
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?
Two compact sentences front-load the main action and follow with a structured return description. No filler or redundant schema repetition.
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 parameterless price tool, the description is complete: it defines the exact symbols, exchanges, and return shape. The presence of an output schema further covers the response details, leaving an agent with everything needed to invoke correctly.
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?
The input schema has zero properties and 100% description coverage by default, so the baseline of 4 applies; the description adds value by explaining what data is returned for the fixed symbol set. There are no parameters to clarify.
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?
States a precise verb ('Get') and a specific resource ('current live prices for all tracked symbols'), then enumerates the exact tracked symbols (ETHUSDT, BTCUSDT, SOLUSDT) and data sources. This clearly differentiates the tool from the fund/bot/strategy siblings.
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?
The description makes the tool's use case self-evident—fetching live market prices—and no sibling tool appears to offer price retrieval, so there is no ambiguity about when to choose it. It does not explicitly contrast it with alternatives, but it provides clear context and no exclusions.
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 target a distinct resource and action, but browse_fund_marketplace and get_marketplace_bots are easy to confuse since both surface marketplace bots with performance metrics. The detailed descriptions clarify their different intents, though the naming does not strongly reinforce the distinction.
The set almost uniformly uses snake_case verb_noun names like create_fund, list_funds, and update_fund_weights. Minor inconsistencies exist, such as get_marketplace_bots returning a list instead of a single item and browse_fund_marketplace using a different pattern from the other marketplace tools.
At 26 tools, the server is on the heavy side and above the typical well-scoped range. The broad domain of funds, strategies, marketplaces, and market data helps justify the count, but several overlapping marketplace/list tools inflate the surface and could be consolidated.
The set covers the core fund lifecycle, roster management, strategy validation/deployment, marketplace browsing, and market data reads quite thoroughly. Minor gaps remain, such as no update/delete operations for strategies and no direct tool for publishing a bot to the marketplace, but these are workable within the existing workflow.