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

With no annotations, the description carries the full burden, and it does disclose one genuinely useful behavioral trait: the output is a prompt pack with examples rather than an executed analysis. However, it omits whether the tool performs any work itself, what happens if the optional query is empty, and whether the 'workflow' is static content or query-scoped. Marketing adjectives ('production-ready', 'run today') substitute for operational detail.

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 two sentences, so nothing is bloated, but the first is entirely promotional framing and the second spends words on 'you can run today' and 'copy-paste'. The one substantive fact — that the deliverable is a prompt pack with examples — is buried at the end instead of front-loaded.

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 structurally simple (one optional param, no output schema, no annotations), so the description does not need to cover much. It conveys the return artifact, which is the main missing piece an agent would otherwise lack. It falls short of complete because it never clarifies that the tool returns static template content versus performing analysis, which is exactly the ambiguity given the adjacent analysis-oriented menu tools.

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 description coverage is 100% for the single optional 'query' parameter, so the schema already explains that it scopes the analysis. The description adds nothing about the parameter — not that it is optional, not what scoping means here — but per the baseline rule, full schema coverage holds this at 3.

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 identifies the subject (takeout menu optimization) and the deliverable (a copy-paste prompt pack with examples), so an agent can infer the output form. But it never states an operative verb such as 'generate', 'analyze', or 'return', and it reads as product marketing rather than a functional statement. With several close siblings (fnb-menu-engineer, restaurant-menu-engineering, sanhao-menu-engineering, menu-cost-calculator, takeout-focused fnb tools), no differentiation is offered.

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 an audience label ('for marketing and operations leaders'), which describes who, not when. There is no condition under which this tool should be chosen over the many menu-engineering siblings, and no exclusion or prerequisite is stated. An agent cannot route between this and fnb-menu-engineer from the description alone.

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