coach

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: the tool returns exactly 3 options, includes specific components (romanization, literal meanings, tone notes, cultural context), and numbers options for use with speak. It does not mention side effects, but for a generation tool, this is sufficient. It could add whether it preserves state or if any action is irreversible, but overall it provides meaningful transparency.

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, front-loaded with the primary purpose, then dense with output specifics. No repetition of schema details or wasted words. Every sentence contributes meaningful information.

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?

The description fully explains what the tool returns and how to chain it with speak, which is critical for context. It lacks details on error cases, language support exceptions, or how the options differ, but given the simple parameter set and the presence of an output description, it covers the essential operational context well. No output schema exists, so the description partially fills that gap.

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 input schema has 100% parameter coverage with clear descriptions for text, context, and target_language. The tool description adds marginal value by illustrating the overall intent ('Express an idea naturally') and the social calibration aspect, which hints at how 'context' might be used. However, it does not explain parameter syntax or provide examples beyond what the schema already gives, so it stays at the baseline.

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 starts with a specific verb and resource: 'Express an idea naturally in a target language.' It then details the output (3 socially-calibrated options with romanization, literal meanings, tone notes, and cultural context), which clearly distinguishes it from sibling tools like speak and replay. The mention of 'numbered for use with the speak tool' further clarifies its unique role in the workflow.

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 when to use this tool: when you want to express an idea naturally in another language and need multiple context-appropriate options. It also gives an explicit integration hint by stating each option is numbered for use with the speak tool, indicating a follow-up action. However, it does not explicitly state when not to use it or contrast with replay, leaving some room for interpretation.

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