earnings_trend

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

With no annotations, the description carries full responsibility for behavioral disclosure. It only implies a read operation via 'get' but does not describe the output format, time range, aggregation method, or any limitations. The description adds no meaningful behavioral context beyond the verb itself, which is already implicit in the tool name.

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 a single short sentence with no filler. It is concise and front-loaded, stating the action and resource immediately. However, it is so terse that it skips necessary context, but for conciseness the structure itself is efficient.

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 tool with one parameter and no output schema, the description should at least clarify what 'earnings trend' means (e.g., historical EPS, revenue over time, vs. a projection) and how it differs from earnings_history. The description is too sparse to fully guide an agent, especially given the large set of sibling earnings tools that could be confused with it.

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 schema covers the single parameter 'ticker' with a description 'Stock ticker', which is self-explanatory. Schema description coverage is 100%, so the baseline is 3. The tool description adds no extra meaning to the parameter, but the schema is sufficient for understanding what to pass.

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 states a specific verb ('get') and resource ('earnings trend') for a ticker, so the basic purpose is clear. However, 'earnings trend' is vague and could be confused with sibling tools like earnings_history or earnings_index. There is no differentiation from these similar tools, so an agent may not know what unique data this returns.

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?

No guidance is provided on when to use this tool versus alternatives like earnings_history or earnings_index. The description gives no context about distinguishing criteria (e.g., trend summary vs. historical detail) and no exclusions. The agent is left to infer usage from the resource name alone.

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