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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses that conditions are ANDed, that top_pct/bottom_pct are deciles of the visible market, and that missing fields cause conditions to fail. It does not mention pagination, rate limits, or the exact return shape, but the output schema exists and the description covers the key behavioral trait of missing-field handling. This is solid but not exhaustive.

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 compact and front-loaded: it states the core function in the first sentence, then lists supported operators, gives concrete example queries, and ends with a critical edge-case rule. Every sentence earns its place, and the structure is easy to scan.

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 the tool's complexity (9 parameters, nested condition objects, multiple operators) and the presence of an output schema, the description is largely complete. It explains the AND semantics, the decile behavior, and the missing-field rule. It could mention the default day ('latest') or the default ordering, but those are already in the schema. The description covers the non-obvious behavioral aspects well.

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%, so the schema already documents all 9 parameters thoroughly. The description adds context about the AND semantics and the decile interpretation of top_pct/bottom_pct, which complements the schema. However, it doesn't add much beyond what the schema already provides for individual parameters, so a baseline 3 is appropriate.

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's purpose: screening the whole market on one completed day with multiple conditions ANDed together. It names the specific resource (market data) and the action (screen), and distinguishes it from siblings like query_cross_section by emphasizing the 'whole market' and 'ONE completed day' scope. The examples of supported conditions and the note about missing fields add further clarity.

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 explains when to use this tool: to answer multi-condition market-wide screening questions on a completed day, with examples like 'top-decile funding with bottom-decile open-interest change'. It doesn't explicitly name alternatives or say when not to use it, but the context signals and sibling names (e.g., query_cross_section, live_market) imply the distinction. The note that a market not reporting a field never satisfies a condition is a useful usage guideline.

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