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

With no annotations, the description carries full responsibility for behavioral disclosure. It lists the output fields, indicates multi-outcome behavior for event_ticker, and highlights the inclusion of settlement criteria. It implies a read-only operation but does not explicitly state safety traits like readOnlyHint or rate limits, though the content is highly informative about what the tool returns.

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 three sentences, front-loaded with the main purpose. Each sentence adds distinct value: an overview, parameter usage modes, and critical context about rules_primary for resolution risk. No unnecessary words or repetition.

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 absence of an output schema, the description explicitly lists return fields and distinguishes between market and event queries. It also emphasizes the importance of rules_primary. It omits edge cases like what happens if both parameters are omitted (since none are required), but it is sufficiently complete for typical usage scenarios.

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% with descriptive parameter definitions. The description adds decision guidance: 'Pass ticker for a single market' and 'event_ticker for all markets in an event (multi-outcome)', and specifies the type of data returned (yes/no bids+asks, etc.). This enriches parameter semantics beyond the schema by clarifying the distinction and expected outputs.

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 clearly states what the tool does: 'Detailed Kalshi market or event info.' It specifies two modes via 'ticker' for a single market and 'event_ticker' for an event, listing concrete return fields (bids/asks, last price, volume, OI, spread, hours until close). This distinguishes it from sibling tools like search or orderbook analysis, providing a specific verb+resource+scope.

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 provides clear context on when to use each parameter: 'Pass ticker for a single market... or event_ticker for all markets in an event.' It also explains that rules_primary text is critical for understanding resolution risk, giving a concrete use case. However, it does not explicitly compare to alternative tools or state when not to use this tool, so it lacks exclusionary guidance.

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