get_market_regimeOne-call market regime classifier: RISK_ON_TRENDING / RISK_OFF / SQUEEZE_RISK / CHOP_LOW_VOL / MIXED. Combines BTC trend + realized vol, Deribit IV premium, funding breadth, and OI-weighted crowding across the top 50 perps. Call this FIRST each session to condition strategy choice.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only and open-world behavior. The description adds value by detailing the composite factors (BTC trend, realized vol, etc.) and the 'one-call' nature, enhancing transparency 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?
Two efficient sentences front-load the output labels and key use-case. Every sentence adds unique value without redundancy. Highly concise and well-structured.
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 zero-parameter tool with clear output labels and no output schema, the description fully covers the necessary context. It explains what the tool does, what it outputs, and when to use it, leaving no gaps.
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?
No parameters exist (0 params, 100% schema coverage), so the description has no burden to explain them. Baseline of 4 applies as the description correctly implies no additional input is needed.
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 states the tool's function as a market regime classifier, lists the specific output labels (RISK_ON_TRENDING, etc.), and differentiates from sibling tools by being a unique composite indicator. The verb 'get' and resource 'market regime' are explicit.
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?
Explicitly instructs to call this FIRST each session to condition strategy choice, providing clear usage context. Lacks explicit 'when not to use' or alternatives, but the directive is strong and sufficient for an agent.
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.