Get the live probability, liquidity, and volume for a prediction market across all venues. Can also return venue order book depth and size-aware VWAP/slippage estimates.
| Name | Required | Description | Default |
|---|---|---|---|
| size | No | USD size for YES-buy VWAP/slippage estimation | |
| market_id | No | Platform-specific market ID | |
| canonical_id | No | Cross-venue canonical market ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It discloses the data returned (live metrics, optionally depth/VWAP) but does not mention any behavioral traits like read-only nature, rate limits, or authentication needs. This is insufficient for a tool with no 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 sentences, 25 words, front-loaded with the core purpose. Every sentence adds value with no redundancy.
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 description covers the main functionality but omits details like parameter relationships (market_id vs canonical_id), return format, and error conditions. Without an output schema, more context would help, but the description is minimally adequate for a 3-parameter tool.
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 description coverage is 100%, so the schema already documents all parameters. The description adds no new semantic info; the mention of VWAP/slippage when 'size' is provided is already stated in the schema. Baseline 3 is appropriate.
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 it retrieves live probability, liquidity, and volume for a prediction market across all venues, with optional depth and slippage estimates. This distinctively separates it from siblings like get_arbitrage, get_history, etc.
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 implies usage for live market data but lacks explicit when-to-use or when-not-to-use guidance. No alternatives are mentioned, though sibling tools differ in function.
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.
Each tool has a clearly distinct purpose: deep link generation, arbitrage detection, historical data, live quotes, unmet demand discovery, and market routing. No two tools overlap in functionality.
All tool names follow a consistent verb_noun pattern with snake_case (execute_url, get_arbitrage, get_history, get_quote, get_unmet_demand, route_market), making them predictable and easy to differentiate.
Six tools is well-scoped for a prediction market surveillance and trading facilitation server. Each tool covers a distinct aspect of the domain without unnecessary bloat or insufficiency.
The tool set covers the full lifecycle from market discovery (route_market, get_arbitrage, get_unmet_demand) to data analysis (get_history, get_quote) to action (execute_url), with no obvious gaps given the server's stated purpose.
