Get social sentiment

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the read-only nature is covered. The description adds behavioral context beyond this: it reveals that sources are 'credibility-weighted platform aggregates, not raw noise,' and lists exact output fields. This is valuable context that complements the annotations without contradicting them.

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 three sentences, with the first sentence front-loading the output fields, the second clarifying the use case, and the third adding a data quality note. Every sentence earns its place with no redundancy or fluff.

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 one-parameter read-only tool, the description is complete: it names the input, lists the key output fields, explains the intended use, and notes data quality. With readOnly and openWorld annotations, no further behavioral disclaimers are necessary. The absence of an output schema is mitigated by the explicit field list.

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?

There is one required parameter, ticker, with no schema description (0% coverage). The description mentions 'for a ticker' but does not specify format or example values. Since the parameter name is self-explanatory in context, the description adds minimal value; a 3 reflects that it is adequate but could be more 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 clearly states it provides 'Current social-media buzz for a ticker' and enumerates the specific output fields (totalMentions, sentimentBreakdown, etc.). It distinguishes itself from siblings by focusing on current sentiment with credibility-weighted aggregates, making the resource and scope unambiguous.

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 a clear usage context: 'Use to read retail attention and crowd sentiment.' This tells the agent when to select this tool. However, it does not explicitly mention alternatives or when not to use it, though the distinct purpose partly differentiates it from sibling tools like get_social_trend or get_social_momentum.

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