Cross-venue disagreement clusters

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

Beyond annotations (readOnly, openWorld), the description discloses orientation methodology ('human/aggregator-reviewed — NEVER price-inferred'), the quality floor for requirePriced (same as CoinRithm's /today page), attribution requirements ('cite CoinRithm when quoting a gap'), and data semantics (graph-clustered, pairwise summaries). This is substantial behavioral context not available from annotations alone.

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 front-loaded with the core purpose and packs meaningful detail into each clause. It is somewhat dense, with the middle sentence listing output fields being long, but overall it is appropriately sized for a data-discovery tool of this complexity.

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 presence of an output schema, the description need not detail return values. It explains the data model, orientation guarantee, parameter default, attribution, and alternative tool, providing complete context for an agent to select and invoke the tool correctly.

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 descriptive parameter fields, so the baseline is 3. The description adds extra context for requirePriced (quality floor, research/debug use) but does not systematically elaborate on other parameters beyond the schema. It provides marginal value over the schema descriptions.

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 returns cross-venue disagreement clusters: prediction-market events matched as the same real-world question across 2+ venues, with one row per cluster. It explicitly differentiates itself from pm_quote for tradability, positioning this as a research/data tool. The resource and scope are unambiguous, though the verb is implicit.

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?

Provides explicit guidance: 'Research/data only: for tradability of one specific outcome use pm_quote.' Also instructs when to set requirePriced false ('only for research/debug') and notes 'No API key required.' This constitutes clear when/when-not and alternative-tool guidance.

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