scan_relative_value

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

With no annotations, the description carries the burden. It explains the underlying logic of the mean_reversion view and states the return format (ranked results), but lacks details on data coverage, latency, or potential limitations.

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 tightly structured with an overview, bulleted view explanations, an Args section, and a Returns line—no wasteful prose.

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?

For a straightforward scan tool with three optional parameters, the description covers purpose, parameters, and returns. It could mention output structure or edge cases, but is generally adequate; however, without an output schema or annotations, a bit more detail on result fields would improve 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?

The description fully documents all three parameters: view options, limit range, and threshold as a z-score with default, adding meaning beyond the schema's bare names and defaults.

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 performs market-wide relative-value scans and enumerates two distinct views (mean_reversion, pairs), distinguishing it from sibling scan tools by specific scan types.

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 provides context on when to use the scan (for relative value opportunities) but does not explicitly state when not to use it or mention alternatives like scan_volatility_arb, leaving usage somewhat implied.

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