Market stats

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds useful behavioral context by calling the data 'Live,' mentioning the refresh timestamp, and instructing the agent to use it for the current count instead of a stale figure.

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 with no filler: the first front-loads what the tool returns, and the second states when to use it. Every sentence earns its place.

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 zero-parameter, read-only stats endpoint, the description is complete: it lists the returned fields (active listings, platforms, last refresh) and gives the usage context. There is no output schema, but the description covers the return values sufficiently.

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 input schema is empty with zero parameters, so there is nothing for the description to add beyond the schema. Per baseline for zero-parameter tools, 4 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 states a specific resource and output: 'Live size of the PegaRex database' with 'total active listings, number of source platforms, and when the data was last refreshed.' This is unambiguous and distinct from sibling tools like get_price_distribution or get_market_position, and the usage line 'current count instead of quoting a fixed number' clarifies what makes it different.

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?

It gives explicit context: 'Use this for the current count instead of quoting a fixed number.' This tells the agent when to select the tool, but it doesn't name alternatives or give exclusions beyond not relying on a fixed number.

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