get_sentiment_velocity

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

Without annotations, the description must disclose behavioral traits. It mentions smoothing and derivative computation but does not clarify if it is read-only, requires paid access, or has rate limits. No side effects or limitations are discussed.

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 very short and to the point, but uses jargon ('d/dt') which may reduce clarity. It conveys key information without excess words, but lacks structure for easy scanning.

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?

For a tool with no output schema and two parameters, the description gives enough context to understand its purpose (early reversal detection). However, it does not explain the output format or how results are interpreted, leaving some gaps.

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 already describes both parameters with 100% coverage, so baseline is 3. The description adds no further parameter details; 'smoothing' may relate to 'window' but is not explicit.

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 states it computes the derivative of sentiment with smoothing for early reversal detection, which clearly identifies the tool's function. However, it does not explicitly distinguish it from sibling sentiment tools like get_sentiment.

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?

No explicit guidance on when to use this tool versus alternatives. The 'Pro tier' and 'Early reversal-detection signal' hint at a specialized use case, but there is no direct comparison or exclusion criteria.

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