kalshi_probability

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

The description reveals that category queries return 'the most active open markets', providing useful behavioral context. However, with no annotations, the description could further disclose details like data freshness or pagination limits to fully compensate.

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 short (two sentences plus example) and reasonably front-loaded, but the first sentence repeats the tool name inefficiently. For a low-complexity tool, it is acceptable and earns its place.

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 no output schema, the description omits return value format or probability interpretation. It adequately introduces two query modes but lacks details on response structure, which is needed for full completeness.

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 adequate descriptions. The description adds an example URL and implies category returns active markets, but does not enhance parameter meaning beyond the schema, such as the format of the ticker or the default limit behavior.

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 the tool returns prediction-market probabilities and specifies two query modes: by category or specific ticker. However, it repeats the opening phrase and does not explicitly distinguish from sibling tools like kalshi_market, which may offer more detailed market information.

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 outlines two usage modes (category or ticker) but does not provide guidance on when to use this tool versus alternatives such as kalshi_market. No when-not-to-use or prerequisite information is given, leaving the agent without clear decision criteria.

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