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

Annotations already declare read-only, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds meaningful context beyond annotations: it specifies seeded CPU sampling and explicitly warns that results are not a real-world forecast guarantee, setting correct expectations about determinism and interpretation.

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 dense sentences with no filler. The main capability is front-loaded, and the important caveat about not being a real-world forecast follows immediately.

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 has five required parameters, no output schema, and no schema parameter descriptions, so the description carries a heavy completeness burden. It names the estimated outputs and the sampling method, but it omits key operational details such as what budget controls, how samples affect runtime or precision, and the allowed uncertainty range.

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?

With 0% schema description coverage, the description must compensate for five undocumented parameters, but it only partially does so. It implies durations are integer-minute tasks capped at 32, uncertainty is a bounded uniform variation, and seed is used for sampling, but budget and samples are never explained, and no parameter ranges or formats are given.

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 ('Estimate') and the exact outputs: deadline success, mean duration, and empirical p95 for integer-minute tasks under bounded uniform variations. It is clear what the tool does, but it does not distinguish itself from siblings like build_robust_plan or improve_schedule, which may also deal with scheduling uncertainty.

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 implies the tool is for simulating plan outcomes under uncertainty, but it offers no explicit when-to-use guidance, prerequisites, or alternatives. An agent must infer that this is appropriate for probabilistic deadline estimation rather than deterministic optimization.

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