compute_power

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

The readOnlyHint annotation already signals a safe read-only operation, and the description adds useful behavioral context by calling it a deterministic engine and explaining the calculation model. This goes beyond the annotation without contradicting it.

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 dense sentence that front-loads the purpose and model, then covers input, output, and use case without wasted words. It is concise yet complete.

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?

There is no output schema, so the description helpfully lists the returned values (power, EDPS, EHP, marginal values). Combined with the schema and annotation, an agent has enough to call the tool correctly, though output structure and edge cases are not detailed.

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 coverage is 100%, so the baseline is 3. The description adds example Chinese keys and the formula model, but the schema already documents attrs, stdAtk, and stdSpeed, including defaults, so no major semantic gap exists.

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 that the tool computes power using a deterministic EHP×EDPS square-root model, takes an attribute panel as input, and returns power, EDPS, EHP, and marginal values. This is specific enough to distinguish it from siblings like battle_simulate or power_curve.

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 explicitly says it is for comparing power before and after changing values, giving a clear intended context. However, it does not mention exclusions or alternatives such as battle_simulate for actual battle behavior.

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