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

No annotations are supplied, so the description carries the full behavioral burden, and it discloses almost nothing: no mutation/read semantics, no prerequisite data, no rate or size limits. The one behavioral hint — that output arrives as a 'copy-paste prompt pack with examples' — is vague and raises more questions than it answers about the actual response payload. 'Production-ready' and 'you can run today' are unverifiable claims, not behavioral facts.

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 short sentences, so length is not a problem, but the opening is front-loaded with positioning language rather than function. Phrases like 'production-ready', 'you can run today' and 'structured, repeatable workflow' add no operational signal and could be deleted without loss.

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, no output schema, and only one optional parameter, the description is the agent's sole source of context — and it omits what the tool returns, what inputs it needs (menu items? costs? margins?), and how results are formatted. The 'prompt pack' framing leaves the agent unable to predict the response shape at all. This is insufficient for even a simple tool.

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?

There is a single optional 'query' parameter with full schema description coverage, so the baseline of 3 applies. The description adds no meaning about how the query scopes the analysis or what format it should take, but the schema already documents the parameter adequately. No information is added or contradicted.

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 text mostly restates the name ('menu cost calculator system') and wraps it in marketing adjectives ('production-ready', 'for marketing and operations leaders') without stating a concrete verb or operation. 'Get a structured, repeatable workflow... delivered as a copy-paste prompt pack' describes a deliverable style, not what the tool actually computes or returns. Against siblings such as fnb-menu-engineer, restaurant-menu-engineering or takeout-menu-optimizer, nothing distinguishes it.

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 only targeting is the audience phrase 'marketing and operations leaders', which is not a use condition. There is no when-to-use, no when-not-to-use, and no reference to any of the many menu/pricing siblings an agent could pick instead. An agent has no basis for choosing this tool over restaurant-menu-engineering or fnb-menu-engineer.

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