future_value_annuity

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states what the tool does ('计算普通年金的未来值') without disclosing any behavioral traits such as whether it's a read-only calculation, error handling, or output format. This is inadequate for a tool with parameters and no annotations.

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, efficient sentence in Chinese ('计算普通年金的未来值'), which is appropriately sized and front-loaded with the core purpose. There is no wasted text, making it concise, though it could benefit from more detail given the lack of other documentation.

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?

Given the complexity (financial calculation with 3 parameters), no annotations, no output schema, and 0% schema description coverage, the description is incomplete. It lacks details on parameter semantics, usage context, and expected output, making it inadequate for effective tool invocation by an AI agent.

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 0%, meaning parameters are undocumented in the schema. The description does not add any meaning beyond the schema—it does not explain what 'payment', 'periods', or 'interest_rate' represent, their units, or how they interact. For a tool with 3 parameters and low coverage, this is insufficient.

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 '计算普通年金的未来值' (calculates the future value of an ordinary annuity) states the specific verb '计算' (calculate) and resource '普通年金的未来值' (future value of an ordinary annuity), which is clear. However, it does not distinguish from sibling tools like 'present_value_annuity' or 'compound_interest', making it vague in differentiation. It avoids tautology by not restating the name/title directly.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention when to prefer this over 'present_value_annuity' or other financial tools in the sibling list, nor does it specify any context or exclusions for usage. This lack of guidance leaves the agent without clear direction.

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