statistica_normality

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 discloses the analytical outputs but says nothing about side effects: whether it opens new output windows, writes result nodes into the spreadsheet, requires a live STATISTICA session, or has runtime limits. For a tool whose 'attach' parameter implies process-level behavior, this is a notable gap.

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 dense sentence that front-loads the resource and then lists the concrete outputs. No filler, no repetition of the tool name. Slightly terse for the amount of structured behavior left unexplained, but structurally clean.

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?

With no output schema, the description usefully enumerates the returned contents (summary plus two named tests plus a histogram), which is real value. However, with 5 parameters, 2 required, and no annotations, it omits input expectations and runtime/side-effect behavior, leaving meaningful gaps 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 40% (only 'attach' and 'intervals' are documented). The description adds no parameter meaning whatsoever, leaving 'path', 'variables', 'sheet', and the required-vs-optional distinction for the agent to guess from bare types. It does not compensate for the coverage shortfall.

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 resource ('normality diagnostics') and enumerates exactly what is produced: descriptive summary, Shapiro-Wilk W, Kolmogorov-Smirnov/Lilliefors, and a histogram. This distinguishes it from broad siblings like statistica_descriptives or statistica_frequencies, though it never explicitly names or contrasts with those alternatives.

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 explains what the tool computes but gives no when-to-use guidance, no prerequisites (e.g., whether a STATISTICA instance must be running, whether data must be loaded), and no routing against the many sibling analysis tools. The agent must infer selection entirely from the tool name.

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