screen_industry

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 reveals that the tool pre-applies the industry filter, which is a key behavioral trait. However, it does not explicitly state that the operation is read-only or non-destructive, nor does it mention any side effects, rate limits, or error behavior. The output format is not described, though an output schema exists. This is adequate but not exceptional.

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 concise and well-structured. It begins with a clear one-sentence summary, followed by a brief rationale, then a structured 'Args:' block with per-parameter explanations. Every sentence earns its place, with no repetition of schema information. It front-loads the core purpose and immediately provides actionable guidance.

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 provides enough information to call the tool correctly: it details all parameters, gives examples, and points to a companion tool for valid industries. Since an output schema exists, the description does not need to explain return structure. It could mention any limits or edge cases, but for a straightforward screening tool, the coverage is sufficient.

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 compensates for the absence of schema descriptions by explaining all four parameters clearly. It gives concrete examples for 'industry' (e.g., 'banksregional', 'biotechnology'), clarifies that 'table' is a metric view like 'Valuation', specifies 'additional_filters' as comma-separated Finviz codes, and defines 'max_results' as the maximum number of stocks. This adds substantial meaning beyond the bare schema titles.

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 verb and resource: 'Screen stocks within a specific industry using Finviz.' It distinguishes itself from siblings by explicitly labeling it a 'convenience wrapper around screen_stocks that pre-applies the ind_ filter,' which immediately clarifies its scope. The use case (peer group analysis, sector deep-dives) further anchors its purpose.

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 direct guidance on when to use this tool: it is a wrapper around screen_stocks specifically for industry filtering, which clearly differentiates it from the general screener. It also instructs to use list_filter_options to look up valid industry codes, establishing a prerequisite action. This makes the selection criteria unambiguous.

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