Veroq

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 successfully documents the cost ('1 credit'), return structures for both modes (list vs. run), and provides a concrete JSON example. However, it omits explicit statements about rate limits, error conditions, or the read-only nature of the operation (implied but not stated).

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 employs a highly structured format with clear headers (WHEN TO USE, RETURNS, COST, EXAMPLE) that front-load critical information. Every line delivers distinct value—purpose, usage context, cost, return payload structure, and example—without redundancy or filler text.

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 simplicity (single optional parameter, dual-mode behavior) and lack of output schema, the description is comprehensive. It compensates for the missing output schema by detailing exactly what fields are returned in both list mode (names, descriptions, filters) and run mode (price, RSI, sentiment, volume), and discloses the credit cost. No critical gaps remain for an agent to invoke this tool effectively.

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%, with the 'preset_id' parameter fully documented in the schema itself. The description adds marginal value by specifying there are exactly '12 presets' and providing a concrete example value ('oversold_tech'), but does not expand significantly on format constraints, validation rules, or semantic meaning beyond the schema's scope.

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 opens with specific verbs ('List' and 'run') and clearly identifies the resource ('pre-built screening strategies' or 'presets'). It implicitly distinguishes from sibling 'veroq_screener' by emphasizing 'without building filters manually,' clarifying this is for pre-built strategies versus custom 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 'WHEN TO USE' section explicitly states the optimal scenario ('quick screening without building filters manually'), effectively contrasting with the manual filter-building alternative (likely 'veroq_screener'). It also clearly documents the dual-mode behavior—omitting preset_id to list all 12 presets versus passing one to execute it—providing unambiguous guidance on invocation patterns.

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