kalshi_implied_probability

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

No annotations are provided, so the description bears full behavioral disclosure. The word 'Calculates' implies a read-only, side-effect-free operation, but the description does not explicitly state that there are no state changes, nor does it describe authentication needs or rate limits. It also does not specify the return format, though it lists several computed outputs.

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 a single, front-loaded sentence that lists the key calculations. There is no filler, and every item mentioned contributes to understanding what the tool returns. It is appropriately sized for a focused calculation tool.

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, the description does list the main returns (implied probability, yields, scenario outcomes, Kelly sizing), giving the agent a good sense of what to expect. The absence of annotations is partially offset by the 'Calculates' phrasing implying safety. Slightly more detail on return structure or edge-case behavior would make it fully complete.

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 input schema already fully documents all six parameters. The description adds no parameter-level meaning beyond what the schema provides. A baseline score of 3 is appropriate when the schema does the heavy lifting.

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 a specific verb (calculates) and a detailed set of resources (market implied probability, payout yields, scenario outcomes, Kelly sizing), making the tool's purpose immediately clear. It does not explicitly differentiate itself from the sibling tools (orderbook, market_search, fee_calculator, cross_spread), but the unique analytical focus distinguishes it implicitly.

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?

There is no guidance on when to use this tool versus alternatives. The description states what it calculates but does not say the context in which an agent should invoke it, nor does it mention exclusions or prerequisites. Usage is only passively implied by the tool name and output list.

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