get_options_ivBTC or ETH options snapshot via free Deribit feed: ATM implied volatility, put-call skew, term structure, total OI and 24h volume. Useful as a sentiment gauge — IV high = market expects big moves; skew indicates direction of hedging.
| Name | Required | Description | Default |
|---|---|---|---|
| asset | Yes | Underlying — Deribit only supports BTC and ETH for the free public feed. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint. Description adds context about the data source (free Deribit feed) and metrics, but does not elaborate on limitations or behavior beyond what annotations imply.
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 concise sentences: first states what the tool does, second explains how to interpret results. No wasted words, front-loaded with key 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 snapshot tool with one parameter and no output schema, the description fully covers purpose, data points, and usage context. No gaps given the tool's 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 covers 100% of the single parameter with enum values and description. The tool description adds minimal extra context (mention of 'free public feed' and Deribit support), so baseline 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?
Description clearly states it provides a snapshot of BTC or ETH options data with specific metrics (ATM IV, skew, term structure, OI, volume). It distinguishes from sibling tools like get_simple_iv by specifying the data source and richness.
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?
Directly explains that the tool is useful as a sentiment gauge, interpreting high IV and skew. While it doesn't explicitly list when not to use, the purpose is clear and distinct from siblings.
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.
Many tools are specialized, but several pairs have fuzzy boundaries: e.g., get_funding_rates vs get_top_funding_rates, get_basic_macro vs get_macro_context, get_simple_iv vs get_options_iv. An agent could easily select the wrong one.
Most tools follow a 'get_X' pattern with descriptive noun phrases. There are a few exceptions like 'create_api_key' and 'search_markets', but overall the convention is consistent and readable.
With 47 tools, the server is overloaded. While the domain is broad, this many tools makes discovery and selection difficult for an agent, reducing coherence.
The tool set covers an impressively wide range: macro data, funding, prediction markets, OI history, whale tracking, risk analytics, position sizing, backtesting, and signal generation. It leaves no obvious gaps for a crypto trading assistant.