get_marketsLive prediction markets from Polymarket and/or HIP-4, sorted by volume. Returns title, YES/NO prices, 24h volume, and expiry.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of markets to return (1–100, default: 20) | |
| active | No | Filter to active/open markets only (default: true) | |
| platform | No | Data source: "polymarket", "hip4", or "all" (default) | all |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint and openWorldHint. Description adds that it returns specific fields and is sorted by volume. Does not contradict annotations and provides useful behavioral context beyond structured data.
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?
Single sentence with all essential information: source, sorting, return fields. No wasted words; highly efficient.
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?
Though no output schema, description explains exactly what is returned. Tool has low complexity (3 optional params) and the description covers purpose, sources, and output fields adequately.
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 coverage is 100% and each parameter is well-described in the schema. The tool description does not add new meaning to parameters beyond mentioning return fields, which is already implied by schema.
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?
Describes specific verb 'get', resource 'markets', sources (Polymarket/HIP-4), sorting by volume, and return fields (title, prices, volume, expiry). Clearly distinguishes from siblings like get_markets_near_resolution and search_markets.
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?
No explicit guidance on when to use this tool vs alternatives like search_markets. The description implies it is for a broad list sorted by volume, but lacks explicit when/why.
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.