query_per_machine_offset

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

With no annotations, the description carries the full burden. It does add one genuinely useful behavioral fact (the offset comes from a calibration profile measured from this printer's real prints and is applied when exact dimensions matter), but it never says what happens when Kiln Pro is absent (error vs. zero offset vs. fallback), nor the shape/units of the returned offset.

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 lead sentence is front-loaded and precise, and the Kiln Pro requirement is worth keeping. The middle sentence is marketing narrative and the trailing pricing URL is agent-irrelevant payload that dilutes the definition.

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?

A four-parameter, fully-undocumented query tool with no annotations and no output schema needs the description to explain parameter meanings and return shape; instead it spends its budget on upsell copy. An agent cannot reliably construct a correct call from this definition alone.

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% and all four parameters are required, so the description must compensate — it does not. Only "specific feature" loosely gestures at feature_class; printer_id, material, and nominal_size_mm (including its unit expectations and valid ranges) are completely unexplained in both schema and prose.

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 first sentence states a specific verb and resource ("Return the calibration offset for a specific feature"), so the agent knows this is a read of a per-feature calibration value. It does not differentiate from close siblings such as get_calibration_freshness, assess_calibration_status, or compute_iso_fit, so the agent must infer where this fits in the calibration family.

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?

"Requires Kiln Pro" plus an upgrade link is an entitlement gate, not usage guidance — it tells the agent nothing about when to prefer this over get_calibration_freshness or explain_calibration_for_design. No when-not conditions, no preconditions about having measured data, no alternatives named.

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