financials_enterprise_value

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

No annotations exist, so the description carries the full burden of behavioral disclosure. It does not state whether the tool returns historical data, what the response format is, whether it respects date ranges, or any limitations. The single sentence adds no behavioral context beyond the bare action, leaving an agent uninformed about side effects or output characteristics.

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, focused sentence with no redundant words. It is front-loaded with the core action and object, making it extremely concise. Given the simplicity of the tool's purpose, this length is appropriate and 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 four parameters, no output schema, and no annotations, the description is severely under-specified. It does not explain what the tool returns (e.g., a time series of enterprise values), how the date range and resampling frame are used, or any potential edge cases. An agent would need to rely entirely on schema descriptions and may still lack a clear mental model of the tool's behavior.

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 100%, so each parameter (to, from, frame, ticker) already has a clear description. The tool description adds no additional meaning about how these parameters interact or what 'frame' resampling implies for enterprise value. Per rubric, baseline 3 is appropriate because the schema fully covers parameters and the description doesn't need to repeat it, but it also doesn't enrich understanding.

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 a specific verb ('Get') and resource ('enterprise value for a ticker'), which precisely identifies the tool's function. It naturally distinguishes from siblings like financials_market_cap or financials_ebitda because enterprise value is a unique metric, so an agent can immediately understand what this tool computes.

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 the many sibling financials_* tools. There is no mention of alternatives, prerequisites, or conditions that would help an agent decide between this and related metrics like market cap or DCF value. The description implicitly suggests it's for enterprise value, but that's already obvious from the name and does not aid in decision-making.

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