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

Beyond readOnlyHint/openWorldHint, the description discloses the commercial model ($0.002 USDC per successful call via x402 on Base/Solana/Arc, failed calls not charged), the data path (Kalshi official public API through a proxy), and the unit semantics (USD per $1 contract, last price = implied probability). Cost and failure-charging behavior are exactly the traits annotations cannot express.

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: what the data contains first, then filters, then provenance/pricing. Every sentence carries information, though the field enumeration overlaps what the output schema likely already declares, making it slightly longer than strictly necessary.

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?

Complete for a zero-required-parameter read tool: an agent knows the source, the fields returned, the filter options, the pricing semantics, and the payment/charging behavior before calling. An output schema exists, so the description need not explain response structure further.

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 all three parameters (limit, series, category) are already documented with examples; the description largely restates them (filter by series ticker or category text) without adding format rules beyond the schema. Baseline 3 is appropriate when the schema carries the parameter burden.

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 resource (Kalshi open events and their markets) and enumerates exactly what comes back: event title, category, series, per-market question, yes/no bid/ask, last price, volumes, open interest, close time, rules. It also identifies the venue as a US-regulated prediction exchange, which no sibling tool covers, so an agent can distinguish it from the crypto exchange/ticker siblings at a glance.

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?

Usage is implied through the two documented filter modes ('Filter by series ticker ... or category text'), which tells an agent how to narrow results, but there is no explicit when-to-use/when-not guidance or pointer to an alternative sibling. Adequate but leaves routing to inference.

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