US Equity Screener

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

Annotations already mark the tool as read-only, idempotent, and open-world. The description adds meaningful behavioral context beyond those hints: the approximate universe size, the filter syntax pattern, raw USD units for money fields, decimal units for margins/growth, and the SIC-label caveat. No contradictions with 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 compact, front-loaded with the purpose, and uses scannable bullets for units and a concrete example. Every section contributes to correct invocation, and the format matches the complexity of the numeric-filter semantics without bloat.

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 output schema exists, the annotations cover safety semantics, and the input schema documents every parameter, the description provides the missing subtlety: units, operator naming, common fields, and the SIC-sector pitfall. An agent has everything needed to call this tool correctly and interpret results.

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 goes well beyond the schema by explaining native units for money fields, ratios, and growth/margin decimals, plus a concrete example. This materially reduces the risk of an agent constructing incorrect filter values like using 10000 for $10B or 25 for 25%.

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 leads with a specific verb and resource: 'Screen ~5-8k US equities by valuation, size, growth and quality.' It clearly distinguishes the tool from siblings like get_quote and get_fundamentals, which target individual securities or metrics rather than broad screening.

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 gives strong context for when to use the tool: when you need to filter a broad equity universe by numeric criteria. It also provides cautionary guidance on the sector field ('Prefer numeric filters unless you know the exact SIC string'). It does not explicitly enumerate alternatives or exclusions, but the use case is clear.

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