news_sentiment_by_ticker

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

With no annotations, the description partially shoulders the burden. It reveals the response format and mentions pagination ('paged'), but omits details like rate limits, authentication requirements, or any side effects. It adequately describes the output shape but not operational behavior.

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 short and includes a JSON-like block for the response format. It is front-loaded with 'Returns normalized sentiment'. While the code block is compact, it could be more readable as prose. Overall, it is efficient but not perfectly structured.

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 complexity (5 parameters, nested objects, no output schema), the description is incomplete. It does not clarify the sentiment score range, pagination details, or how this tool differs from sibling tools like news_by_ticker or sentiment screeners. Lacks sufficient context for full use.

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 0%, but the description does not explain parameters beyond showing the response structure. It does not describe ticker, date_from, date_to, or limit. The schema itself has minimal descriptions (e.g., YYYY-MM-DD for dates). The description adds little to parameter understanding.

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 it returns normalized sentiment and outlines the response structure including ticker, name, series, and format options. This distinguishes it from sibling tools like news_by_ticker (news articles) and sentiment screeners by focusing on per-ticker sentiment data. However, it does not explicitly contrast with these siblings.

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 no guidance on when to use this tool versus alternatives such as news_by_ticker or screener_sentiment. It lacks any context about prerequisites, typical use cases, or when not to use it.

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