List calculators, converters, experiments and educational Labs

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, covering safety and side effects. The description adds behavioral context by stating it lists every Lab and includes formulas, assumptions, and citation URLs; this goes beyond the annotations without contradicting them.

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 dense sentences: the first front-loads the action and payload, the second gives the use case and filter condition. There is no repetition of schema or annotation data and no filler.

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 simple list tool with one optional enum parameter, strong annotations, and an output schema, the description covers what is returned, why to use it, and when to apply the filter. The output schema handles return-structure details.

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 only provides an optional kind enum with 0% description coverage, so the description must carry the meaning. It says the parameter filters by kind and maps it to the exact user intents: calculator, converter, experiment or educational game. The enum itself lists allowed values, so deep per-value explanation is not necessary.

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 action and resource: 'List every SANTISMM Lab', and names what each entry contains: inputs, outputs, assumptions, formulas and citation URL. This distinguishes it from get_lab and other list/get siblings by promising a complete enumeration with a defined payload.

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?

Explicitly frames it as a discovery tool: 'Use this to discover interactive and machine-readable tools' and says to 'filter by kind when the user specifically asks for a calculator, converter, experiment or educational game.' It gives clear when-to-use context, though it does not state when to prefer get_lab or search_all instead.

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