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

With no annotations provided, the description carries the full burden of behavioral disclosure, and it discloses nothing. It does not state what the tool computes, what it returns, whether it reads from conversation context, or any edge cases. The operation is completely opaque — an agent cannot predict the call's behavior or output.

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 not meaningfully concise — it is under-specified, repeating the tool name twice around a colon ('Ohms Law V: Ohms Law V'). Its only sentence is wasted on restating the name rather than conveying information, which is the opposite of front-loaded, purposeful structure. Like the 'Process' example, this is under-specification, not conciseness.

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?

This is a physics-calculation tool with zero parameters, no annotations, and no output schema — the agent needs description to explain invocation and return behavior, and the description supplies none. An agent cannot tell how to provide inputs (e.g., via context), what output format to expect, or how this differs from ohms-law-i/r. The definition is completely inadequate.

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 has zero properties, so per the rubric baseline (0 params = 4), there are no parameter semantics for the description to clarify. The description adds no meaning, but the schema trivially covers everything since there is nothing to document. The deeper ambiguity about where input values come from (with no parameters) belongs to contextual completeness rather than parameter semantics.

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 'Ohms Law V: Ohms Law V' is a pure tautology — it restates the tool name and title without defining any verb, resource, or behavior. An agent cannot determine that this tool calculates voltage via V = I × R, nor can it distinguish it from siblings x402-ohms-law-i and x402-ohms-law-r. This is exactly the tautology failure mode from the calibration examples.

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?

There is zero guidance on when to use this tool versus alternatives. No mention of the sibling tools ohms-law-i or ohms-law-r, no condition like 'use this when voltage is the unknown,' and no exclusions. An agent facing hundreds of x402 siblings gets no routing help whatsoever.

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