Generate Type Scale

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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, destructiveHint), so the description's job is to add behavior beyond that. It does: 'Deterministic real output' assures the agent the result is computed and genuine rather than a placeholder or sample, and the fluid clamp() behavior ('scales display type down on small screens') plus the emitted @theme block describe the output's runtime behavior. No contradiction with annotations — generating a scale as output is consistent with read-only, idempotent, non-destructive hints.

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?

Three dense, front-loaded sentences with zero filler: purpose and output contents first, then output format, then the behavioral guarantee and companion tools. Every sentence earns its place and the most decision-relevant information (what the tool generates) appears immediately.

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?

There is no output schema, so the description carries the burden of explaining return values — and it does, covering the named steps, sizes, line-heights, letter-spacing, CSS custom properties, and Tailwind @theme block. All 4 parameters are optional and fully documented in the schema, and the annotations disclose safety and idempotency. The only minor gap is that it doesn't explicitly state the output is returned as text/CSS for the agent to consume rather than written to files, but readOnlyHint largely covers that.

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 100%, so the baseline is 3 with the schema doing the heavy lifting. The description adds marginal connective meaning — 'from a base size and ratio' maps to the base and ratio params, 'optional fluid clamp()' maps to the fluid boolean, and 'named steps (xs…6xl)' clarifies the steps param — but these largely restate what the schema already documents in adequate detail. No critical param semantics are added beyond the schema.

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 names a specific verb and resource ('Generate a modular typographic scale from a base size and ratio') and enumerates the exact deliverables: named steps (xs…6xl), sizes, line-heights, letter-spacing, and optional fluid clamp(). It distinguishes itself from siblings like generate_color_system and generate_design_tokens by specifying its precise output surface (CSS custom properties and a Tailwind v4 @theme block), leaving no ambiguity about what this tool produces.

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 closing line, 'Pair with suggest_font_pairing and generate_design_tokens,' gives concrete workflow context that positions this tool within a broader design-token pipeline. It implies when to use it (typography scale generation) via the focused subject matter, but it does not explicitly state when not to use it or which sibling (e.g., generate_design_tokens) would be the better choice for broader token needs. Clear context, no exclusions.

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