Cross-venue disagreement clusters

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

Annotations only supply readOnly/openWorld/destructive hints; the description adds substantial context beyond them: the orientation is human/aggregator-reviewed and NEVER price-inferred, the requirePriced quality floor mirrors the public /today page, no API key is required, and there is a citation request. This tells the agent what the data means and can be trusted for.

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?

Effectively front-loaded with what the tool is and what one row covers, and every sentence is load-bearing (quality floor, orientation review, sibling routing). It is dense almost to the point of being a wall of text, which slightly hurts scannability, but no sentence is wasted.

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?

With 9 all-optional parameters, an output schema, and safety annotations, the description supplies everything the remaining burden requires: methodology, trust/orientation guarantees, the requirePriced quality floor, and when to prefer pm_quote. Nothing needed to call it correctly is missing.

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 description coverage is 100%, so the schema already documents each parameter thoroughly (enums, defaults, bounds). The description's detailed magnitude commentary (referenceProbability, weightBasis, maxOverallGap) actually describes return fields covered by the output schema, not input parameters, so it adds little input-level meaning. Baseline 3 is correct.

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?

States a specific verb+resource: cross-venue disagreement clusters of prediction-market events CoinRithm matched as the same question across 2+ venues, graph-clustered so one row covers all venues. It explicitly distinguishes itself from siblings (pm_quote for single-outcome tradability) and from forecast/play-money venues. An agent can tell what it returns without opening the 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?

Gives clear routing: 'Research/data only: for tradability of one specific outcome use pm_quote,' plus a conditional on requirePriced ('pass false only for research/debug'). It establishes the intended use and the one named alternative, though it does not differentiate from other pm_data_* siblings (pm_data_overview, pm_data_canonical).

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