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

Annotations already establish readOnlyHint and openWorldHint, so the safety profile is covered. The description adds real behavioral context the annotations cannot: the output is non-executable displayed probabilities, not arbitrage claims, and the values must be validated against depth, fees and fills. It omits freshness/latency or matching-confidence caveats, which keeps it short of a 5.

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?

Front-loaded with the core action and the result shape, then caveats, then routing. Every sentence carries weight, though the displayed-probabilities point is restated twice ('Returns displayed probabilities' and 'Displayed probabilities only'), a minor redundancy.

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?

An output schema exists, so return values need no explanation, and the description supplies the remaining essentials: research-only framing, the non-executable nature of the data, the filtering parameter, and the alternative tools for executable pricing. Nothing needed to call this correctly is missing.

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 both parameters and the baseline is 3. The description reinforces that query filters keywords in the market question but adds nothing for limit or for matching semantics (what makes two events 'equivalent'), so it does not exceed the baseline.

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 a specific verb and resource (compare candidate equivalent events on Polymarket vs Kalshi) plus the returned signal (displayed probabilities and their spread). It also names the sibling tools it is not (list_executable_opportunities, compare_executable_quotes), so an agent can distinguish it without opening the schema.

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?

Explicitly routes the agent: use this for displayed probabilities in research mode, and use compare_executable_quotes or list_executable_opportunities when executable all-in prices are required. It also states the precondition for acting on results (verify order-book depth, fees, fills, resolution rules), which is clear when/when-not guidance.

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