social_trending

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

With no annotations, the description fully carries behavioral disclosure. It warns that trending can be manufactured attention, clarifies that rank and watcher counts are vendor pass-throughs with no AlphaDesk scoring, and notes the social source can be off by default. This is unusually transparent.

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 result, then adds caveats and usage guidance in a logical escalation. Every sentence adds meaning; there is no filler or repetition of schema fields.

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 one-parameter read-only tool with no output schema, it provides enough context: what the data means, where it comes from, how to interpret it, and what to pair it with. It also includes the return concepts of rank and watcher counts.

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 only parameter, limit, has no description in the schema and is not mentioned in the tool description. However, the integer type and default of 30 make it reasonably self-explanatory, so the gap is minor for a single optional parameter.

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 identifies exactly what is returned: symbols people are talking about, in StockTwits' own rank order with its own figures. It explicitly distinguishes this from news by stating it measures attention, not news, which differentiates it from siblings like symbol_news and movers.

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?

It gives explicit guidance: use it to decide what to look into, never as a reason itself, and pair it with filing_feed, symbol_news, or trading_halts to verify whether anything actually happened. This is actionable when-to-use and when-not-to-use guidance.

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