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

Building on annotations readOnlyHint=true and openWorldHint=true, the description adds useful behavioral context: 'Free, no key', 'live', and the fact that pre-launch S&P 500, Nasdaq 100, and Treasury-yield series are also included. It does not contradict the annotations and adds value beyond what the structured fields alone convey.

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 front-loaded with the core purpose and follows with output details, parameter hints, and example queries. It is longer than strictly necessary, mostly due to an extensive parenthetical list of series, but each section earns its place and the structure is logical.

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 carries the burden of explaining return content, and it does so thoroughly: open-window status, two-sided mid YES price, close time, target price, settlement condition, and settled-up share over the last 96 windows. Combined with full parameter schema coverage and read-only annotations, an agent has enough context to invoke the tool correctly.

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 baseline is 3. The description goes slightly beyond the schema by providing concrete alias examples ('eth', 'KXETH15M', 'natural gas') and by clarifying that 'series' selects one market while 'asset_class' filters. This helps an agent map user intent to parameters more reliably.

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 concrete resource (Kalshi 15-minute up-or-down markets) and a clear action: list or filter them live. It enumerates the data returned (open window, YES price, close time, target price, settlement basis, settled-up share), and mentions pre-launch series. This is specific enough to distinguish it from any sibling tool without opening 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 explicit usage context with example user queries ('what is the ETH 15 minute market doing', 'which Kalshi 15-minute markets are open', 'KXBTC15M price now') and tells the agent to pass 'series' for one market or 'asset_class' to filter. It does not explicitly name alternatives or exclusions, but the intended use cases are clear and actionable.

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