hig_check_liquid_glass

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the risk profile is covered. The description adds useful behavioral context beyond annotations: the result is provenance-aware ('Apple's vs. community/Figma-derived') and includes a checklist. No contradiction with 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 front-loaded with a one-sentence purpose, then a dense but non-redundant list of covered guardrails, and clear Args/Returns sections. Every sentence earns its place and there is 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 read-only, single-purpose lookup tool, the description covers inputs, selection semantics, and return contents. An example input/output would be a small enhancement, but the output schema and annotations already provide enough structure.

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?

With 0% schema description coverage at top level, the description compensates by explaining both params.context ('where the material is applied') and params.platform ('selects blur budget') with valid values. It adds selection semantics that are not obvious from the schema alone.

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 states a specific verb ('Return') and resource ('Liquid Glass guardrails'), then names the exact constraint categories it covers. It is clearly distinct from sibling tools like hig_get_tokens, hig_swiftui, and hig_fetch.

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 implies use when checking Liquid Glass design budgets and mentions 'agents routinely get wrong', but it never explicitly says when to choose this tool over alternatives or when not to use it. Sibling differentiation is left to inference.

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