engineering.weibull_reliability

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

With readOnly/idempotent/openWorld annotations already covering the safety profile, the description adds useful behavior: parameter domain constraints (β,η>0, time≥0, time=0→R=1), the explicit exclusion of a location parameter γ, and 30-significant-digit precision. This is solid value beyond the annotations, short only of edge-case response details.

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?

Four dense sentences with zero filler; the formula and domain constraints are front-loaded, followed by the β-interpretation, the γ exclusion, and precision note. Every sentence adds distinct 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?

For a 3-parameter pure-math tool with an output schema (so return values need no explanation), the description covers purpose, domain constraints, precision, and the location-parameter limitation. The only minor gap is routing guidance to the exponential sibling for the β=1 case.

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 coverage is 0% (params are bare strings with title only), so the description must carry semantics—and it does: it defines shape β, scale η, and time in η's units, including the domain constraints for each. It does not explain the string typing (arbitrary precision), leaving a minor gap.

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 (계산한다/calculates) and resource (2-parameter Weibull reliability R(t) and unreliability), including the exact formula. An agent can identify the operation clearly, though it doesn't explicitly name the closest sibling (engineering.exponential_reliability) to differentiate.

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 β interpretation guidance (β<1 infant mortality, β=1 random, β>1 wear-out) implies the appropriate diagnostic context, but there is no explicit statement of when to prefer this over exponential_reliability or other reliability siblings, and no when-not-to-use guidance.

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