Polymarket MCP Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions what data is returned ('event details, including associated markets'), it doesn't disclose important behavioral traits like whether this is a read-only operation, potential rate limits, authentication requirements, error conditions, or response format. For a tool with zero annotation coverage, this is a significant gap.

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 extremely concise and well-structured: a clear purpose statement, source guidance, and an example - all in just two sentences. Every element earns its place with no wasted words, making it easy for an AI agent to parse quickly.

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 (single parameter lookup), 100% schema coverage, but no output schema and no annotations, the description is adequate but incomplete. It covers the basic purpose and parameter source but lacks behavioral context about the operation's safety profile, response format, or error handling. For a read operation with no output schema, more detail about what 'event details' includes would be helpful.

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 description coverage is 100%, so the schema already documents the single 'id' parameter with its type and description. The description adds minimal value beyond the schema by providing an example ('Example: id=80505') and indicating the source ('Source: id from list_events'), but doesn't add substantial semantic context. This meets the baseline for high schema coverage.

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: 'Get event details by id, including associated markets.' This specifies the verb ('Get'), resource ('event details'), and scope ('including associated markets'). However, it doesn't explicitly differentiate from sibling tools like 'get_event_by_slug' or 'get_event_markets', which reduces it from a perfect score.

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 for when to use this tool: 'Source: id from list_events.' This indicates the parameter should come from the list_events tool. However, it doesn't explicitly state when NOT to use it or mention alternatives like 'get_event_by_slug' for slug-based lookup, so it falls short of a perfect score.

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