Live prediction market odds, implied probabilities and betting-market data from Polymarket — give a market id or slug, get each outcome with its probability (0-1), volume, liquidity and resolution status. Price: $0.05 per call (x402 payment, USDC on Base mainnet).
| Name | Required | Description | Default |
|---|---|---|---|
| market | Yes | Polymarket market id or slug, e.g. '2654605' or 'will-it-rain-tomorrow' |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It honestly discloses the pricing model and payment method ($0.05 per call, x402 payment, USDC on Base mainnet), and clarifies that data is live. It does not mention rate limits or error behavior, but the payment disclosure is a significant behavioral trait beyond the schema.
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 purpose and ending with actionable pricing/payment info. Every clause adds value, with no redundancy or filler.
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?
The tool is simple (one parameter, no output schema), and the description covers input requirements, output contents, and cost. It lacks a detailed output structure or error-handling info, but for a lightweight data-retrieval tool the description is sufficient.
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 schema has 100% coverage for the single 'market' parameter, including examples. The description essentially restates 'give a market id or slug' without adding further syntax or format details, so it does not go beyond what the schema already provides.
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 states a specific verb+resource: get live prediction market data from Polymarket. It clearly lists the output components (probability, volume, liquidity, resolution status) and distinguishes this tool from the crypto/sanctions-focused siblings by naming the unique data source.
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 clear context on what to supply (market id or slug) and what to expect in return. It does not explicitly mention alternative tools or exclusions, but none of the sibling tools offer comparable Polymarket data, so the usage context is sufficient.
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.
There is notable overlap between crypto_pre_trade_verdict and solana_pre_trade, both providing pre-trade decisions for Solana. The agent_rank_check and agent_visibility_audit are also similar in purpose but differentiated by depth. However, descriptions are detailed enough to clarify the intended use, so ambiguity is moderate.
Tool names consistently use snake_case and often include domain prefixes like crypto_, solana_, and agent_. Minor deviations exist, such as solana_pre_trade lacking the 'verdict' suffix seen in crypto_pre_trade_verdict, and standalone names like gleif_lei and polymarket_odds that don't follow a domain-prefix pattern. Overall, the style is predictable and readable.
With 10 tools, the server is well-scoped within the ideal 3-15 range. Each tool serves a distinct purpose or tier (e.g., quick check vs. deep audit), and the count feels appropriate for a multi-purpose utility server without being overwhelming or sparse.
The server covers several domains, but each has gaps. For example, there is no dedicated wallet address sanctions screening tool (only fused into crypto_pre_trade_verdict), no token price or market data tool outside of the dossier, and no agent search or listing functionality. However, the core risk-check workflows (token safety, pre-trade, agent visibility) are reasonably well-covered with both quick and detailed tiers.