Cross-venue prediction-market statistics

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

Beyond the read-only annotation, the description discloses source-aware freshness, per-venue volume basis, restriction to real-money venues for monetary totals, self-computed nature requiring citation, and the absence of authentication. These are significant behavioral caveats that meaningfully inform usage.

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 moderately long but well-structured: purpose first, then alternative, freshness, caveats, and authentication. Each sentence adds necessary information, though it could be slightly trimmed without losing value.

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 read-only statistics tool with an output schema, the description is comprehensive. It covers the metrics returned, venues included, freshness behavior, health resource, monetary caveats, and attribution requirements—leaving no major gaps.

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 already provides complete coverage for the single fiat parameter (description + default). The tool description adds context about monetary totals but no additional parameter-level detail, so the schema carries the full burden.

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 provides cross-venue prediction-market statistics, enumerates specific metrics (market counts, volume, liquidity), and lists all 12 venues. It distinguishes itself from siblings by explicitly directing users to pm_data_event for full event evidence.

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 an explicit alternative ('Use pm_data_event for full event evidence'), clearly implying when this overview tool is appropriate. It also notes that no API key is required, and points to a separate health endpoint for freshness details.

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