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

Annotations already confirm this is a safe, read-only, idempotent calculation. The description adds value beyond annotations by disclosing the exact formula (F=k·x), input units (N, m), and output unit (N/m), which helps the agent verify correctness.

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?

Five short sentences, front-loaded with the key action and formula, with zero filler. The final pointer to list_bundles is useful context rather than noise.

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?

The tool is simple, the output schema exists (so return values needn't be explained), and annotations cover safety. The description still includes units, formula, and a related-resource pointer, leaving no meaningful gap for an agent to call it correctly.

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 parameters are already fully documented. The description reinforces units but adds no semantic detail beyond what the schema provides. Baseline 3 is appropriate.

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?

States a specific verb (Compute) and resource (spring constant k) with the underlying formula, making it clear it solves for k rather than force. It does not explicitly differentiate from the sibling calculate_force, but the target variable is unambiguous.

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?

Provides a broad context ('Use for physics or mechanical design') but no explicit when-to-use vs when-not-to-use or alternative tools. Implied usage only, with no exclusions or routing to calculate_force for the inverse problem.

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