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

The description adds substantial behavioral context beyond the read-only/idempotent annotations: it discloses that Kalshi fees are not modeled, that spreads are gross rather than net tradeable edges, that null temporal alignment means 'could not be computed' rather than 'aligned', and that compatibility warnings may be non-empty even when pairs are returned. It also explains the skipped/unclassified leg behavior. This is exemplary transparency.

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 long but well organized with clear labeled sections (RESPONSE, SAFETY FIELDS, Codes) and is front-loaded with the core purpose and modes. Most sentences carry substantive safety or matching information. It earns its length for a complex comparison tool, though it is not as lean as it could be.

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 complexity of the tool, the absence of an output schema, and the many caveats around matching and compatibility, the description is essentially self-sufficient. It covers response structure, safety fields, code semantics, fee limitations, skipped-leg behavior, and temporal alignment meanings. An agent has enough context to call the tool and interpret results 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?

With 100% schema description coverage, the baseline is 3, but the description adds meaningful interaction semantics: it explains that topic mode auto-fetches matching events, explicit ticker/slug mode is for custom pairings, and both modes run identical matchers with the same disclosures. This clarifies how the three optional parameters relate to each other beyond the schema's individual 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 opens with a precise statement of what the tool does: it reports the cross-venue spread between Kalshi and Polymarket for the same resolving question. It goes on to specify the two invocation modes and the matching logic, which clearly separates it from siblings like polymarket_arbitrage and polymarket_edges. The scope is specific enough that an agent can tell what this tool uniquely contributes.

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?

The description gives strong contextual guidance: it explains when to use topic mode versus explicit ticker/slug mode, states that both modes run the same matcher, and warns that pre-mapped topics frequently return compatibility warnings and are not automatically tradeable. It does not, however, explicitly name sibling tools as alternatives or state precise when-not-to-use conditions, so it stops short of full alternative routing.

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