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

With no annotations, the description carries the full burden. It discloses key behaviors: solves closed-form equations, rounds upward to manufacturing increment, re-runs the evaluator, and grants no authority. It also explicitly lists operations it does not perform, giving the agent a clear picture of side effects. It does not mention failure modes or edge cases, but these are largely covered by the schema constraints.

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 two sentences with no wasted words. The main action is front-loaded, and the second sentence efficiently lists limitations. It is dense but readable, earning a high score for 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?

Despite having an output schema, the description leaves out key parameters (load_n, span_mm) and does not specify the exact acceptance criteria fields. For a 9-parameter tool with no schema descriptions, the agent needs more explicit parameter guidance to invoke the tool correctly. The description covers the overall workflow but is incomplete for robust usage.

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 0% description coverage, so the description must explain parameters. It references purpose, load model, width, elastic modulus, acceptance criteria, and manufacturing increment, but omits two critical physical inputs: load_n and span_mm. It also fails to name the specific acceptance criteria fields (max_deflection_mm and allowable_stress_mpa), leaving agents to infer them from the schema. This is insufficient for a tool with nine parameters.

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 states a specific verb ('derive'), a specific resource ('prismatic rectangular beam height'), and clarifies it is 'proposal-only.' It distinguishes from sibling tools by explicitly listing what it does not do (optimization, material selection, network calls, fabrication), making it clear it is a pure sizing calculation.

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?

It provides contextual guidance by labeling the output as 'proposal-only' and listing exclusions (no general optimization, no engineering authority), which helps an agent understand when not to rely on this tool. However, it does not explicitly name alternative sibling tools (e.g., validate_rectangular_beam_section_derivation) or state conditions under which to choose them, so it leaves some inference to the agent.

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