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.

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

With no annotations, the description carries the full burden. It clearly states the action (replays last spoken audio) and implies a non-destructive operation. It does not address edge cases like absence of prior audio, but the behavior is straightforward.

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 the verb front-loaded. Every word earns its place, with no filler or redundancy.

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 parameterless tool with no output schema, the description adequately covers purpose and usage triggers. It could mention behavior when no audio clip exists, but the simplicity of the tool makes this a minor 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 tool has zero parameters, so the description is not required to explain parameter details. The baseline of 4 applies, and the description adds no unnecessary parameter information.

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 uses the specific verb 'replay' with the resource 'last spoken audio clip', clearly indicating the action and scope. It distinguishes well from sibling tools like 'speak' and 'coach' by focusing on repetition of prior audio.

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 lists trigger phrases ('again', 'replay', 'repeat', 'play it again') to indicate when to use the tool, providing clear context. However, it does not explicitly name alternatives or mention when not to use it.

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

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

No annotations are provided, so the description must disclose behavioral traits on its own. It states that the tool 'Generates audio and plays it through speakers,' which is the core behavior. However, it does not mention side effects such as network requirements (edge-tts is an online service), whether it returns a value, or what happens if audio cannot be played. This is partial transparency, but not comprehensive.

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 two concise sentences. The first sentence front-loads the primary purpose and behavior, and the second gives usage timing. Every word earns its place, and it is appropriately sized for the tool's simplicity.

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 tool is simple, with thorough parameter descriptions in the schema and a concise explanation of behavior and usage. There is no output schema, but the description makes clear the result is audio played aloud. It lacks deeper details like error handling or edge cases, but for this complexity it is sufficiently complete.

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%; each of the four parameters has a meaningful description. The tool description adds no extra parameter semantics—it only provides overall context. According to the rubric, with high schema coverage the baseline is 3, and the description does not elevate it.

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 clearly states the tool's function with a specific verb and resource: 'Speak text aloud using text-to-speech.' It also provides context for when to use it ('Use after coach'). However, it does not explicitly distinguish this tool from sibling 'replay', which could be an alternative for hearing audio, so it stops short of full differentiation.

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 gives clear usage context by stating 'Use after coach to hear how a phrase sounds.' This implies the workflow and when to invoke this tool. It does not exclude other sibling tools like replay, but the context is sufficient for typical usage. No explicit alternatives are mentioned, so it is not a 5.

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