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

No annotations are provided, so the description carries the full behavioral burden. It hints that the deliverable is a 'prompt pack' with a prompt, usage guide, and edge-case handling, but says nothing about whether invocation is read-only, what the response looks like, or how the optional query affects output.

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?

Only three short sentences, but the opening line ('Turn expertise into output') and 'produce professional results in minutes' are promotional filler that delay the actual subject. The useful clause about contents is buried at the end.

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?

With no annotations and no output schema, the description should explain what invoking returns and how the optional query scopes it. It instead describes the artifact in generic sales language, leaving the agent without the operational detail needed for a confident call.

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% and the single optional 'query' parameter is documented in the schema as scoping the analysis. The description adds no meaning beyond that, which matches the baseline for fully described schemas.

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 restates the name with marketing framing ('voice tpl tool prompt pack', 'Turn expertise into output') rather than stating a concrete verb and resource. It never says what the tool actually produces or how it differs from the sibling ir-voice-gen-tool and ir-voice-check-tool, so an agent cannot pick it on purpose alone.

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?

It names an audience ('restaurant and brand teams') but gives no when-to-use condition, no exclusions, and no reference to the gen/check siblings. An agent must infer the use case entirely from the tool name.

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