Market data: stock news

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

With no annotations, the description does useful work by naming Finviz and TradingView as sources, explaining that Finviz headlines carry price reactions, and noting that headline titles are matched to report overlap. It still omits operational behavior such as provider failure handling, rate limits, or whether the call is always read-only.

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 front-loaded with the core purpose, then cleanly separates source behavior, arguments, and return structure. Every section adds useful information without padding.

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 three-parameter read-oriented market data tool with an output schema, the definition covers the important source behavior, parameter meanings, and shape of the returned data. It is not fully complete on failure modes or rate-limit behavior, but no major decision-critical context is missing.

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%, so the description must compensate, and it does: limit is defined as maximum headlines per provider, include_reactions is tied specifically to requesting Finviz reaction columns, and symbol is identified as the ticker. The only minor gap is that it does not further explain the effect of include_reactions=false on the returned fields.

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 starts with a specific verb and resource: dual-sourced headlines for one ticker. It identifies the two providers and the overlap concept, making the tool clearly distinct from quote, price, screener, and analysis 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?

Usage is only implied by the purpose: fetch news headlines for a ticker. There is no explicit when-to-use guidance, no when-not-to-use guidance, and no named alternative such as stock_why_moving for causal analysis.

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