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

With no annotations, the description carries the transparency burden and does a good job: it explains the default window (today), the optional sector filter, and interprets the result as an attention proxy. It doesn't detail result ordering/limits, but 'most-mentioned' implies the key 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?

Two sentences, front-loaded with the core output, default behavior, optional filter, and a use-case hook. No filler or repetition.

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 simple two-parameter query tool, the description is complete enough: it identifies the output, default behavior, optional filter, and a clear user scenario. No output schema exists, but the tool's purpose is simple enough that return format is not needed for correct invocation.

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. It explains both parameters: date_range defaults to 'today' and sector is an optional filter. It doesn't specify allowed date formats or sector values, but adds meaning beyond the bare schema names.

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 the tool returns the most-mentioned tickers in the news over a window, optionally filtered by sector, and frames it as a market-attention proxy. This distinguishes it from siblings like news_latest/news_trending by focusing on 'top mentions' and gives a concrete use case.

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?

Provides explicit invocation guidance ('Call this when the user asks which stocks are getting the most buzz or where the crowd's focus is today'), which gives clear context for when to use it. It lacks exclusions or named alternatives, so it doesn't fully reach the 'when-not' bar.

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