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

Annotations already declare readOnlyHint true and destructiveHint false, and the description adds meaningful behavioral context: it returns qualitative tags and a link-out to Kalshi, while explicitly excluding raw market data. This clearly communicates what the tool does and does not expose.

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 well-structured and front-loaded with the core definition, followed by return details, exclusions, usage guidance, and filter options. Every sentence contributes meaningful information without redundancy, making it appropriately concise for the tool's complexity.

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 adequately describes the returned items as carrying signal tags and a link-out, and clarifies the data exclusions. It covers use cases, examples, and filters, but could be slightly more explicit about the exact item shape or sorting behavior, though the provided info is likely sufficient.

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?

The schema covers the signal, category, and vertical parameters with descriptions, leaving only 'limit' without prose. The description restates the three filter dimensions but does not add new parameter semantics beyond what the schema already provides, so it meets the baseline for high schema coverage.

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 this tool returns Storyflo stories that match actively traded event contracts on Kalshi, distinguishing it from market-data tools by emphasizing it is an editorial sourcing surface. It also names the specific qualitative signal tags and link-out behavior, making the purpose unambiguous.

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 explicitly says 'Use this when the agent needs to know which Storyflo stories are about news themes that have an actively traded event contract' and provides examples. It also includes a when-not by stating the tool 'never returns raw prices, market-implied probabilities, volumes, or open interest,' though it does not name sibling alternatives.

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