Explain Market Conditions

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive. The description adds valuable context: explicit statement that it does not claim causation, that it includes observed metrics and associated_changes, and that the model should produce the natural-language explanation—beyond the safety profile provided by 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?

Two sentences with zero waste. The main purpose and key behavioral caveat are front-loaded, and each sentence 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?

The tool has an output schema (has output schema: true) so return structure is covered. The description clearly explains the comparison window concept, the default baseline, and the expectation of model-generated explanation. It is complete for a read-only analytical tool, though it could mention edge cases or error behavior.

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% and includes a description for baseline_start; the description adds minimal parameter detail beyond confirming the default baseline window, which is already in the schema. The baseline of 3 applies because the schema does the heavy lifting.

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?

States a specific verb ('Returns structured evidence') and resource ('market conditions in a focus window versus a baseline window'). Explicitly differentiates from siblings by noting it does not claim causation and that the calling model should produce the explanation, which is a clear distinguishing behavior.

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?

Provides clear context: use for comparative analysis of market windows, and that the model must generate the explanation. However, it does not explicitly name alternatives or state when not to use it, so it lacks explicit exclusions.

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