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

With no annotations provided, the description carries the behavioral disclosure burden. It does disclose a non-obvious behavior: 'Returns warnings for inconsistent inputs instead of failing' and guarantees formula parity with the published calculator. This is sufficient for a simple calculation tool.

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 three concise sentences with no filler. It front-loads the core purpose, then provides formula consistency and error-handling behavior, with every sentence adding value.

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 description covers the calculation purpose, output metrics, formula consistency, and error behavior. Although there is no output schema, the description names the computed values, so an agent knows what to expect. The main omission is the exact return structure, but that is minor for a simple deterministic calculation.

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?

All six parameters already have meaningful descriptions in the schema, so schema coverage is 100%. The tool description adds no parameter-level detail beyond the schema, which matches the baseline expectation of 3.

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 uses a specific verb ('Compute') and a clear resource ('Overall Equipment Effectiveness from shift data'), then lists the exact output components (availability, performance, quality, OEE). The sibling tools are all unrelated knowledge/profile/protocol tools, so there is no ambiguity about what this tool does.

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?

The description clearly frames when to use the tool: when OEE must be calculated from shift data. It additionally notes consistency with the published calculator, which is useful context for users deciding between this and manual computation. There are no similar sibling tools, so explicit exclusions are unnecessary.

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