get_pricesGet current spot prices (USD) and 24-hour percentage change for all 13 tracked crypto assets: BTC, ETH, SOL, XRP, HYP, DOGE, LINK, AVAX, HBAR, LTC, BNB, DOT, SUI. Prices are sourced from major exchanges and refreshed frequently.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true and openWorldHint=false, and the description adds meaningful behavior: prices are sourced from major exchanges, refreshed frequently, and returned for all 13 assets. This is sufficient for a simple read-only snapshot and does not contradict any annotation.
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 tight sentences front-load the result content and scoping information. The enumerated asset list is necessary to define the fixed universe, and there is no filler or redundant wording.
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 no-input, read-only tool with no output schema, the description covers the key semantics: the exact data fields, the USD denomination, the fixed 13-asset universe, and freshness expectations. Nothing essential is missing for correct invocation.
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?
This tool has zero parameters, so the schema already fully covers the input surface. The description consequently needs no parameter elaboration, and the baseline 4 for a no-parameter tool 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 uses a precise verb-resource pair ('Get current spot prices... and 24-hour percentage change') and explicitly scopes the result to all 13 tracked assets by listing them. This makes it clearly distinguishable from sibling tools focused on flows, index, and analytics.
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 does not name sibling alternatives, but the content ('spot prices', '24-hour percentage change') makes the appropriate use case unmistakable against the flow/analytics siblings. No exclusions are stated, but for a zero-parameter read-only tool the context is clear enough.
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 has a clear primary focus: single-asset historical flows, composite sentiment index, latest cross-sectional flows, prices, and weekly aggregation. The only minor overlap is between get_flows_summary and get_weekly_analytics, but their descriptions make the distinction obvious.
All tool names follow a consistent get_<noun> pattern using snake_case, with clear descriptive suffixes like asset_flows, flows_summary, and weekly_analytics. There is no mixing of conventions or vague verbs.
Five tools is well-scoped for a read-only crypto ETF analytics server. Each tool covers a distinct data need without redundancy, and the count is appropriate for the narrow domain.
The set covers the core query surface for ETF flow data: recent daily snapshot, single-asset history, weekly aggregates, sentiment index, and prices. Minor gaps exist, such as no multi-asset historical comparison or explicit asset list endpoint, but these are unlikely to cause major agent failures.