Return step-by-step instructions for setting up x402 USDC autopay for this MCP server. Use this if a paid tool returned a 402 error or you're onboarding a new agent that needs to pay for API calls. Free.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It correctly identifies the tool as returning instructions and being free, but lacks details on output format or any potential rate limits. However, given the tool's simplicity (zero parameters), the disclosure is sufficient.
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?
The description is two sentences, front-loaded with the core action, and every word adds value. No redundancy or unnecessary detail.
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, simple instruction-returning tool, the description covers purpose and usage context adequately. It could mention the return format (e.g., text) but is otherwise complete.
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?
The input schema has zero parameters and 100% coverage, so the description does not need to add parameter details. The baseline of 4 applies, and the description offers no extra param information, which is acceptable.
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 verb ('return') and the resource ('step-by-step instructions for setting up x402 USDC autopay'), and the context signals show no sibling overlaps, making its purpose distinct.
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 specifies when to use ('if a paid tool returned a 402 error or you're onboarding a new agent') and notes it is free, providing clear guidance against alternatives.
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.
Most tools occupy distinct roles (install, usage stats, wallet setup), but list_endpoints and pricing_info overlap substantially: both report paid endpoints and prices, even though one emphasizes live status and the other detailed fees/payment networks. Descriptions help separate them, but an agent could still pick the wrong one for a pricing question.
Names are uniformly snake_case and readable, but the pattern is mixed: install_snippets and list_endpoints use verb_noun, while pricing_info, usage_stats, and wallet_helper use noun-based names. This is a readable mixed convention rather than a chaotic one.
Five tools is a reasonable number for a small server, but for a product called 'Prediction Market Data for AI Agents' the set is oddly scoped: everything is onboarding/pricing/usage meta-tools rather than data tools. The count is not excessive, but it feels thin for the apparent market-data purpose.
The server promises prediction market data, yet none of the five tools retrieves markets, odds, prices, positions, or any actual market data. Even if the free helper tools are complete, the core data surface is entirely absent, leaving agents with no way to fulfill the server's stated purpose.