Cross-venue prediction-market statistics

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

Annotations already declare the read-safe, open-world profile, but the description adds substantial context the annotations do not: no API key required, freshness is source-aware with per-venue lag/health, monetary totals cover real-money venues only, and aggregates are self-computed requiring attribution to CoinRithm. These are meaningful operational caveats beyond the structured hints, though it does not describe rate limits or payload shape.

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 lead sentence front-loads what the tool is and the metrics it returns, and the remaining sentences each add a distinct caveat (sibling routing, freshness, venue basis, attribution, auth). It is dense and long for a one-parameter read tool, but there is little waste.

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?

An output schema exists, so return values need not be re-explained, and the description covers scope, freshness semantics, monetary caveats, attribution, and auth. Combined with the schema it is essentially complete for correct invocation, with only minor ambiguity about the 'compact discovery shape'.

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?

With schema description coverage at 100% and a single optional fiat parameter already documented in the schema, the description does not need to carry parameter burden. It only implies that fiat governs monetary figures, which the schema already states, so the baseline 3 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 names a specific resource (cross-venue prediction-market statistics) and enumerates the exact metrics returned (total/open/closed market counts, total and 24h volume, liquidity) plus the full list of 12 venues. It explicitly distinguishes itself from the pm_data_event sibling, so an agent can tell them apart without opening either schema.

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 names one alternative with its selecting condition: 'Use pm_data_event for full event evidence.' It also points to /api/prediction-markets/sources/health for per-venue freshness, which is real routing guidance. It does not, however, disambiguate against the many other pm_data_* siblings (volume_history, disagreements, calibration), so the guidance is clear but not exhaustive.

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