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

Annotations already mark the tool read-only and non-destructive, so the safety profile is covered. The description goes well beyond that: spreads are gross not net because Kalshi fees are not modeled, compatibility_warning and compatibility_codes can be non-empty even when matched_pairs>0, null temporal_alignment means 'could not compute' rather than 'aligned', and legs with unknown metric_type/match_subtype are never paired. No contradiction with annotations.

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 dense; nearly every sentence carries a distinct operational fact, and labels like 'TWO MODES', 'RESPONSE', 'SAFETY FIELDS', and 'Codes' provide internal structure. It could be formatted with bullets or shorter paragraphs for easier scanning, but the complexity of the matching and safety semantics justifies most of the length.

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 a nontrivial response, the description covers the response shape, safety codes, per-entry flags, skipped counters, fee caveats, and the exact meaning of null temporal_alignment. An agent has enough context to invoke the tool and interpret ambiguous results without additional documentation.

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?

The schema already covers all three parameters at 100%, so the baseline is 3. The description adds meaningful cross-param semantics: BOTH modes run the identical token-overlap matcher, and explicit kalshi_event_ticker/polymarket_event_slug values override the topic-mapped side. This helps the agent reason about interactions that the schema alone does not convey.

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 verb–resource pair: it computes the cross-venue spread between Kalshi and Polymarket for the same resolving question. That scope distinguishes it from sibling tools like polymarket_arbitrage or polymarket_edges, and the two modes are explicitly named and described.

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 explains when to use the pre-mapped topic shortcuts versus explicit ticker/slug pairings, and warns that pre-mapped topics are often not tradeable ('pre-mapped ≠ tradeable', 'most pre-mapped topics return compatibility_warning today'). It does not explicitly name alternative tools or state hard when-not-to-use conditions, but the guidance is concrete and actionable.

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