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

With no annotations, the description carries the full burden and does well: it declares units (millimetres), the exact linearity law ('the field is exactly linear in turns x current, so only that product changes the answer'), and the provenance behavior including the off-grid lane-hub fallback. It does not state that the call is a pure/deterministic computation with no side effects, but nothing misleading is present.

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 dense but front-loaded with the purpose, then the returned quantities, then the one genuinely non-obvious behavioral fact (provenance.canonicalUrl). The long enumeration of return quantities partially duplicates the existing output schema, which is the only real slack.

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 four-parameter physics solver with two required inputs, all ranges, and an output schema, the description supplies the missing context an agent needs: units, the turns×current invariance, geometry applicability, and the validity caveat for the closed form. Because an output schema already exists, its detailed return enumeration is redundant rather than necessary, keeping this from a 5.

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 the schema already documents turns, current, length and diameter including defaults and the turns×current linearity. The description reinforces the millimetre units and the linearity rule but adds no new parameter-level syntax or format beyond what the schema provides, so baseline 3 applies.

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 opens with a precise verb+resource: 'Solve the on-axis magnetic field of an air-core solenoid,' and anchors it to a concrete artifact ('the identical function behind the /lab/solenoid table'). The sibling tools (biquadDesign, gaussianBeam, roomModes, etc.) occupy entirely different domains, so there is no ambiguity to disambiguate.

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?

Usage is implied rather than stated: the agent can infer you call this when you need an on-axis solenoid field, and the 'closed form should not be used below this turn count' caveat is embedded in the returned data rather than the guidance. There is no explicit when-to-use/when-not statement and no named alternative or prerequisite.

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