quartiles

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it explains what quartiles are, it doesn't describe how the tool behaves: whether it sorts input data, handles non-numeric strings in the 'numbers' array, returns errors for empty arrays, provides output format, or has any computational constraints. For a statistical tool with zero annotation coverage, this is a significant 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?

The description is appropriately concise with two sentences that directly address the tool's function. It's front-loaded with the core purpose and avoids unnecessary elaboration. However, the parenthetical domain/category note adds minor redundancy without enhancing clarity for tool selection.

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 tool's statistical nature, no annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't explain input requirements, error conditions, output format, or behavioral details. For a tool that performs calculations on data arrays, more context is needed to ensure correct invocation.

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?

The input schema has 0% description coverage, with one parameter 'numbers' of type array of strings. The description adds no information about this parameter—it doesn't explain what 'numbers' represents, expected format (e.g., numeric strings), handling of invalid entries, or example usage. With low schema coverage, the description fails to compensate, leaving parameters largely undocumented.

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 quartiles of a dataset (Q1, Q2/median, Q3). Divides data into four equal parts.' It specifies the verb ('calculate'), resource ('quartiles'), and output details. However, it doesn't explicitly differentiate from sibling tools like 'percentile' or 'comprehensive_stats', which could provide similar statistical calculations.

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 domain ('statistics') and category ('general'), but offers no explicit when/when-not instructions, prerequisites, or comparisons to sibling tools like 'percentile' or 'median'. This leaves the agent without clear usage context.

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