suggest_microcopy

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

No annotations are provided, so the description carries the full burden. It states the tool suggests microcopy and returns context-aware suggestions but does not disclose any constraints, side effects, or changes to state. As a generative suggestion tool, this is minimally adequate.

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 concise sentences with no redundant words. The first sentence states the core purpose, the second adds output types. Perfectly front-loaded for AI consumption.

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 tool with 3 simple parameters and no output schema, the description covers the essential behavioral aspects. It could mention that suggestions are returned as text strings, but the generative nature makes format less critical. Adequate for the complexity.

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 coverage is 100%, so the schema already documents all 3 parameters. The description adds only the phrase 'context-aware', reinforcing the role of the context parameter. This adds marginal value 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 explicitly states the tool's function: suggesting user-friendly microcopy for UI elements. It names specific outputs (buttons, labels, messages, help text). This clearly distinguishes it from sibling tools like suggest_error_message or suggest_form_pattern.

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 usage: when you need microcopy for UI elements. It does not explicitly state when not to use it or compare to siblings, but the purpose is clear enough that an AI agent would correctly infer applicability.

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