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

The description goes well beyond the annotations by disclosing concrete behavioral details: Polymarket as primary source, Kalshi as fallback, expiry tolerance relative to horizon, liquid-strike filtering, monotonicity enforcement, interpolation at spot, supported symbols, and null behavior when no market exists. No contradiction exists with the readOnly/destructive annotations.

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 a single dense sentence with no filler. The core definition is front-loaded, and each clause adds necessary operational detail: source, fallback, strike selection, interpolation, supported assets, and null case. This is appropriately sized for the 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?

The description is complete for a read-only probabilistic lookup tool. It covers data sources, fallback behavior, filtering rules, supported symbols, and edge-case null output. An output schema exists, so return-value documentation is not required in the description.

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 the baseline is 3. The description adds meaningful context for how parameters drive the calculation: the expiry window is tied to horizon_days, spot is the interpolation point, and symbol support is enumerated. This enriches but does not duplicate the schema descriptions.

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 defines the tool's purpose: computing a prediction-market implied probability that a token trades higher than its current price at a given horizon. Though it lacks an explicit verb like 'calculate' or 'fetch,' the resource and concept are specific. It does not explicitly distinguish itself from sibling tools, though the prediction-market angle differentiates it implicitly.

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?

No guidance is given about when to use this tool versus alternatives such as price_crosscheck or positioning_check. The description implies usage for market-implied probability, but it does not state conditions, exclusions, or alternative routing. Without that, an agent has to infer appropriateness from the tool name and surrounding context.

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