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

The description goes far beyond the read-only/idempotent annotations by detailing safety fields, compatibility codes, temporal mismatch semantics, skipped comparisons, and the fact that spreads are gross of Kalshi fees. It discloses that legs with unknown metric types are never paired and that keyword-based pairing is unverified. This is rich, actionable behavioral disclosure with no contradiction to the 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 front-loaded with the core purpose and modes, and it is organized via labeled sections. It is, however, very long and dense, covering many edge cases and code lists in one continuous block. Nearly every sentence carries information, but the sheer volume makes it less concise than ideal for quick agent consumption.

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?

There is no output schema, so the description carries the burden of explaining return values, and it does so thoroughly: leg prices, top_spreads_pp, compatibility fields, temporal_alignment, skipped counters, fees_note, and low_confidence_pairs are all described. It also warns about signal validity and non-equivalent bet shapes, giving an agent enough context to call and interpret 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%, so the schema already documents each parameter. The description adds value by explaining that both the topic and explicit modes run the identical token-overlap matcher, by listing the ten valid topic shortcuts, and by clarifying override behavior. This is more than the schema alone provides, though not extensive extra parameter detail.

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 names the exact resource: the cross-venue spread between Kalshi and Polymarket for the same resolving question. It distinguishes the tool from siblings like polymarket_arbitrage by making the Kalshi–Polymarket pairing and same-event matching explicit. The two modes are also clearly stated, so an agent knows what the tool actually fetches and compares.

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 clear usage context: use the topic shortcuts for pre-mapped macros or provide an explicit kalshi_event_ticker plus polymarket_event_slug for custom pairings. It also warns that pre-mapped topics may return compatibility warnings and are not automatically tradeable. However, it does not explicitly contrast this tool with sibling alternatives or say when not to use it.

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