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

No annotations are provided, so the description carries the full behavioral burden. It only names the computed outputs and says nothing about authentication (api_key), side effects, determinism, rate limits, or how the simulation parameters (n_samples, confidence) affect the run.

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?

A single short imperative sentence with the key concept ('ICH Q8 design space') front-loaded. Every word carries information, though the parenthetical output list is slightly dense and the fragment could be structured for easier scanning.

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 complex statistical computation with 6 parameters, no annotations, and 0% schema coverage, the description leaves critical input semantics, prerequisites, and usage context unexplained. The existing output schema relieves it of explaining return values, but the input side remains largely undocumented.

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 0% across 6 parameters, and the description adds no meaning for data, api_key, n_samples, confidence, factor_columns, or response_specs. With zero schema documentation and no compensating explanation, an agent cannot infer the required input formats.

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 a specific resource ('ICH Q8 design space'), with the computed outputs (NOR, PAR, probability of meeting specs) named. It clearly identifies the domain concept, though it does not explicitly contrast itself with related DoE siblings like covadoe_optimize or covadoe_find_optimum.

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 gives no indication of when to use this tool versus alternatives such as covadoe_find_optimum, covadoe_optimize, or covadoe_predict. There are no prerequisites, no conditions, and no exclusions stated.

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