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

No annotations are provided, so the description carries the behavioral disclosure burden. It does communicate that data is real-time, sports-focused, and sourced from Kalshi, and it names two distinct request modes. However, it does not disclose behavior when no args are provided, possible data_type values, or potential limitations/errors, which matters because all parameters are optional.

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 two sentences with no filler. The primary purpose is front-loaded, and the parameter usage follows immediately. Every sentence contributes necessary guidance.

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 output schema exists and the parameter set is small, the description covers the essential call patterns well. It explains the main two usage modes and the data source. Minor omissions like full data_type enumeration and handling of empty arguments are present, but they do not prevent a competent agent from invoking the tool correctly in most cases.

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 0%, so the description must compensate. It does explain event_ticker and milestone_id roles and gives a concrete data_type value, which is useful. But it only mentions one data_type value and does not clarify allowed values, defaults, or whether event_ticker and milestone_id are mutually exclusive, leaving significant gaps.

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 identifies the tool's action ('fetch'), resource ('real-time sports game statistics, play-by-play data, and live event feeds'), and source ('from Kalshi'). It is specific enough to distinguish this from siblings like orderbook or forecast tools without needing to inspect their schemas.

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 actionable usage guidance: use event_ticker for event charts, or milestone_id with data_type='game_stats' for play-by-play. It provides clear context for when to use this tool, though it does not explicitly state exclusions or compare against sibling tools.

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