Cross-venue prediction-market statistics

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

Annotations already indicate readOnly=true and openWorldHint. The description adds critical behavioral context: freshness is per-venue independent, volume reported on venue basis, monetary totals are self-computed aggregates requiring citation, and no API key needed.

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 well-structured and front-loaded with the main purpose. It is slightly lengthy but every sentence adds value, except some redundancy about venue names could be trimmed.

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 output schema exists, the description thoroughly covers what data is included, freshness model, volume methodology, citation requirement, and authentication status. It also points to the health endpoint for more detail.

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 coverage is 100% with a single optional 'fiat' parameter. The description adds that monetary figures are reported in this currency but does not significantly expand beyond the schema description. Baseline score applies.

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 provides 'Free public cross-venue prediction-market statistics' listing specific metrics (counts, volume, liquidity) and all 11 venues. It distinguishes from sibling tools like pm_data_event or pm_data_whales by being an aggregate overview.

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 use for broad market stats and notes no API key required, but does not explicitly state when to use this tool versus alternatives like per-venue health endpoints or individual market data tools.

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