standard_deviation

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

No annotations are provided, so the description carries full burden. It states what the tool does but lacks behavioral details: it doesn't mention input validation (e.g., handling non-numeric strings in the 'numbers' array), error conditions, performance characteristics, or output format. The description is minimal and does not compensate for the absence of 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 concise and front-loaded: the first sentence states the core purpose. The second sentence adds context (relationship to variance), and the parenthetical provides domain categorization. There is no wasted text, though it could be more structured (e.g., separating usage notes).

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?

Given the complexity (statistical calculation with two parameters), lack of annotations, 0% schema description coverage, and no output schema, the description is incomplete. It does not explain parameter semantics, behavioral traits, or output format. For a tool with undocumented parameters and no structured guidance, the description should provide more context to be adequate.

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%, so the description must compensate. It mentions 'a list of numbers' which aligns with the 'numbers' parameter, but does not explain the 'population' parameter (whether to use population or sample standard deviation). The description adds minimal meaning beyond the schema, failing to clarify parameter purposes or usage.

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 clearly states the tool's purpose: 'Calculate the standard deviation of a list of numbers.' It specifies the verb ('calculate') and resource ('standard deviation'), and adds domain context ('Domain: statistics, Category: general'). However, it does not explicitly differentiate from sibling tools like 'variance' or 'comprehensive_stats', which is why it's not a 5.

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 provides no guidance on when to use this tool versus alternatives. It mentions the relationship to variance ('The square root of variance'), but does not indicate when to choose standard deviation over variance or other statistical measures like 'z_scores' or 'comprehensive_stats'. There are no explicit when/when-not instructions or named alternatives.

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