All Hyperliquid perp markets with mark price, funding APR, open interest, 24h volume, and basis, sorted by volume, open interest, or funding. Send { limit?, sort? }. Full derivatives market map for trading agents. [x402 paid tool — price $0.005; POST /api/perps/markets]
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | "volume" (default), "oi", or "funding" | |
| limit | No | Max markets, default 25 (max 200) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the full burden. It discloses it's a paid tool (price $0.005), uses POST, and returns sorted data. It does not discuss permissions, rate limits, or side effects, but for a read-only data tool this is adequate.
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?
Three sentences, no wasted words. First sentence defines purpose and data fields, second explains parameters, third adds pricing and endpoint. Every sentence serves a purpose.
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?
Given no output schema, the description sufficiently describes the return data (mark price, funding APR, open interest, 24h volume, basis) and sorting behavior. It also includes pricing and HTTP method, making it complete for an agent.
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?
With 100% schema coverage, the description adds value by restating parameter options in a concise format ('Send { limit?, sort? }') and clarifying the default sort. The schema already explains parameters, but the description's shorthand aids quick understanding.
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 explicitly states it returns 'All Hyperliquid perp markets' with specific fields (mark price, funding APR, open interest, 24h volume, basis) and sorting options. This clearly distinguishes it from sibling tools like perps_funding or perps_basis which focus on individual data points.
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 provides context by stating it's a 'Full derivatives market map for trading agents,' implying it's a broad overview. It does not explicitly exclude other use cases or name alternatives, but the presence of sibling tools for specific data offers implicit guidance.
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.
Tools are organized by domain prefix (e.g., 'crypto_', 'rh_', 'snipe_'), which helps distinguish between areas. Within each domain, they serve distinct purposes, though some overlap between domains exists (e.g., price data appears in multiple groups). Overall, an agent can navigate effectively.
All tool names follow a consistent snake_case pattern with a domain prefix and a verb_noun combination (e.g., 'compliance_risk', 'rh_stock', 'snipe_honeypot'). This makes the API predictable and easy to explore.
With 159 tools, the server is extremely large. While the broad scope of web3 and utility functions justifies many tools, the count is significantly above the typical range for a coherent toolkit, potentially overwhelming agents and increasing selection error.
The toolkit covers a wide range of web3 operations: crypto, DeFi, compliance, safety, scheduling, memory, etc. There are no obvious major gaps for its intended purpose, though some niche areas might be missing.