get_prediction_arbitrage

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

No annotations are provided, so the description carries the full burden. It does disclose two valuable non-schema facts: it scans live data and costs $0.05 USDC per call. It omits latency, behavior when no edges clear the threshold, and result shape, which matter for a paid analysis tool.

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?

Two sentences, zero padding, with the capability statement first and the cost disclosure last. Every clause earns its place.

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 no output schema and no annotations, the description does supply the essentials: data source, analytic output, supported domains, and price. It stops short of describing result contents or edge cases, but an agent has enough to call it 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 description coverage is 100%, so the schema already documents limit, category, and minEdgePercentage with defaults; baseline 3 applies. The description's category list does add example domains, but it names 'elections' while the schema enumerates 'pop-culture', a mild inconsistency rather than added clarity.

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 specific verbs (scans, calculates) and a specific resource (live Polymarket prediction markets) plus the output class (+EV discrepancies, arbitrage spreads vs consensus models). That is enough to distinguish it from search_prediction_events (lookup) and get_whale_macro_signals (macro signals), though no sibling is named explicitly.

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?

Usage is only implied: an agent infers this is for finding arbitrage/positive-EV opportunities rather than listing events. The price note ($0.05 USDC) usefully signals this is a paid call worth weighing against free siblings, but there is no explicit when-to-use/when-not or alternative routing.

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