Polymarket Agent Mcp

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: orders sit until filled, distinguishes between preview/simulation vs live/real orders, and mentions it's a 'Pro feature' (implying potential access restrictions). However, it doesn't cover rate limits, authentication needs, error conditions, or what happens in edge cases (e.g., if no favorites exist).

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 perfectly concise and front-loaded: three sentences that each earn their place by explaining the core action, operational behavior (preview/live modes), and feature tier. Zero wasted words or redundant information.

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 the tool's moderate complexity (financial trading with preview/live modes), no annotations, and no output schema, the description does well by covering the core purpose, behavior, and mode distinction. However, it lacks details on return values, error handling, and specific prerequisites (e.g., account setup, market hours), leaving some gaps for an AI 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?

Schema description coverage is 100%, so the schema already fully documents both parameters (discount_pct, bet_size) with ranges, defaults, and descriptions. The description adds no additional parameter semantics beyond what's in the schema, maintaining the baseline score of 3.

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 tool's purpose with specific verbs ('place limit orders', 'simulates', 'places real CLOB orders') and resources ('WTA tennis match favorites', 'order book'). It distinguishes itself from siblings like orders.buy/sell by specifying it's for 'stink bids' at a discount on a specific market (WTA tennis).

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 about when to use this tool: for placing discounted limit orders on WTA tennis favorites. It distinguishes between preview and live modes. However, it doesn't explicitly state when NOT to use it or name specific alternatives among sibling tools (like orders.buy for regular orders).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.