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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds useful behavioral context by stating the tool returns every lab and enumerating the included fields (inputs, outputs, assumptions, formulas, citation URL). It does not mention pagination or ordering, but the presence of an output schema and openWorldHint softens that 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?

Two sentences, front-loaded with the primary action and return contents, followed by a clear usage note. Every sentence earns its place and there is no redundant phrasing.

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 single-optional-parameter list tool with an output schema and comprehensive annotations, the description is complete: it states what is returned, when to use it, and how filtering works. Nothing essential is missing for an agent to select and invoke this tool 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?

The schema provides an enum for kind but has 0% description coverage, so the description must add meaning. It does: 'filter by kind when the user specifically asks for a calculator, converter, experiment or educational game' ties the parameter to user intent and lists the exact categories. It slightly under-specifies what happens when kind is omitted, though 'List every SANTISMM Lab' implies the unfiltered behavior.

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 opens with a specific action and resource: 'List every SANTISMM Lab with its inputs, outputs, assumptions, formulas and citation URL.' This clearly distinguishes list_labs from the many sibling list_* tools by naming the unique resource (Labs) and the exact content returned.

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 tells the agent when to use the tool: 'Use this to discover interactive and machine-readable tools.' It also explains when to use the kind filter: 'filter by kind when the user specifically asks for a calculator, converter, experiment or educational game.' It does not explicitly name a sibling like get_lab as the alternative for retrieving a single lab, but the discovery framing is clear enough.

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