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 adds critical context not found in the schema: 'COST: 1 credit' (rate limiting) and a detailed 'RETURNS' section describing the per-sector data structure (ticker count, brief count, average sentiment). It lacks details on caching or data freshness, but covers the essential behavioral traits.

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 excellently structured with clear section headers (WHEN TO USE, RETURNS, COST, EXAMPLE) that front-load critical information. Every sentence and section earns its place; there is no fluff or redundancy. The formatting makes it easy for an agent to quickly parse intent and constraints.

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 low complexity (1 optional parameter) and lack of output schema, the description compensates effectively by detailing the return structure in the 'RETURNS' section. It covers purpose, usage context, cost, input example, and output format—providing complete information necessary for correct invocation despite missing structured output metadata.

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 input schema has 100% description coverage for the single 'days' parameter ('Lookback period in days (default 7)'). The description provides an example usage '{ "days": 7 }' which reinforces the schema but does not add additional semantic meaning, syntax constraints, or value ranges beyond what the schema already documents. Baseline 3 is appropriate for high schema coverage.

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 explicitly states the tool 'Get[s] a sector overview with aggregate sentiment scores and brief counts across all market sectors.' This provides a specific verb (Get), resource (sector overview), and scope (across all market sectors, aggregate level), clearly distinguishing it from ticker-specific siblings like veroq_ticker_analysis.

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?

Includes an explicit 'WHEN TO USE' section stating it's for 'a macro view of which sectors have the most bullish or bearish news coverage' and 'sector rotation analysis.' While this provides clear context for appropriate use, it does not explicitly name alternative tools (e.g., veroq_ticker_analysis) for when users need non-aggregate data.

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