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

The annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered by structured fields. The description's one behavioral addition is the claim that a real algorithm engine executes the computation rather than an LLM, which is meaningful trust context. It says nothing about what the goodness-of-fit return looks like, what sample-size or minimum-data assumptions apply, or how ties/non-numeric input are handled, so it adds only modestly beyond the annotations.

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 short clauses plus a return-value note, front-loaded with the operation label, with no filler or repetition. Every element carries signal, though the bracket-prefix duplicates the annotation title and the parenthetical engine claim is somewhat tangential to invocation. Efficient overall.

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 small read-only tool with two fully-described parameters and no output schema, the description covers the what and a hint of the return (goodness of fit), which is close to adequate. What is missing is the set of supported distributions for 'dist' and any note on input requirements, both of which an agent needs before calling. Given the low complexity, a 3 reflects minimum viability rather than a serious deficiency.

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 100%, so both parameters are already documented in the schema and the baseline of 3 applies. The description adds no meaning beyond that: it does not list which distribution names are accepted for the 'dist' parameter (there are zero enums, so this is the main gap the prose could have filled), nor does it constrain the numeric string array. No compensating information is provided.

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 bracketed tag names the operation (distribution fit test) and the following clause states the concrete user question it answers: is the data normal, and what distribution does it follow. That is a specific verb-plus-resource framing that an agent can match against a request, and it is distinguishable from neutral summary siblings like act_data_quick_stats or act_stat_center. It stops short of a 5 because it never states the method family or scope (single column, one-variable-at-a-time) explicitly in the prose, only via the schema.

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 an implied trigger, namely when a user asks whether data is normal or which distribution it follows, which is genuine usage guidance for routing. However, it names no alternative tools and no exclusions, so an agent cannot tell when it should prefer act_data_quick_stats, act_ic50_fit, or act_stat_center instead. Usage is inferable but not disambiguated.

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