get_global_stats

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

With no annotations, the description carries the burden of behavioral disclosure. It reveals that the tool combines two subgraphs and emphasizes 'accurate' volume/fee/trade data, which is useful context. It does not mention return format or potential latency, but for a simple no-parameter read operation, it provides sufficient transparency.

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 concise sentences, front-loaded with the primary purpose. The second sentence adds essential detail about data sources without unnecessary words.

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 no-parameter tool, the description covers the key aspects: what it returns (aggregate stats), which data sources, and specific metrics. It lacks an explicit return format, but given the simplicity and the mention of the included stats, it is nearly 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 tool has zero parameters, so the schema is fully complete by definition. The description adds no parameter information, but none is needed. Baseline for 0 params is 4.

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 aggregate Polymarket platform statistics and specifies the exact data sources (Main and Orderbook subgraphs) and metrics (market counts, volume, fee, trade data). This distinguishes it from sibling tools like get_global_open_interest or get_daily_stats.

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 when to use this tool—when aggregate platform-wide statistics are needed, with a note about combining sources for accurate volume/fee/trade data. However, it does not explicitly mention alternatives or when not to use it.

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