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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds that these values feed search_results, but does not say whether the list is static or dynamic (i.e., whether a source can disappear if it stops producing results) or how large it typically is. Useful but not rich behavioral context.

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 short sentences, zero waste. The what (sources) comes first, the concrete examples anchor it, and the consumption instruction closes it out.

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?

With no output schema, the description carries the burden of conveying return values, and the three examples do that well. The only remaining gap is whether the list is exhaustive/stable or reflects only sources currently producing results — a minor omission for a very simple tool.

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 tool takes zero parameters, so the schema baseline is 4. The description goes slightly beyond by explaining what the returned tokens mean and where they are consumed, which is the relevant semantic information for a parameterless tool.

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?

Identifies the resource precisely ('sources that have produced results') and immediately grounds it with concrete example values (twitter_spaces, tweets_en, tweets_ja), which makes the unit of the list unambiguous. It is clearly distinguishable from siblings like search_results, though the verb is implied rather than stated.

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?

Explicitly tells the agent what to do with the output: 'Use one as the `source` argument of search_results.' This is a real routing instruction to a named sibling. It lacks any when-not guidance, but for a zero-parameter enumeration tool there is little alternative to exclude.

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