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

No annotations are supplied, so the description carries the full disclosure burden, and it discloses almost nothing: no indication of what the tool actually does at runtime, what it returns, or whether it consumes the query only to scope a prompt pack. The phrases "production-ready" and "repeatable workflow" are marketing claims, not behavioral facts an agent can rely on.

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?

At two sentences it is short, but nearly every phrase is sales copy ("production-ready", "Get a structured, repeatable workflow you can run today") rather than actionable information. It is under-informative rather than over-long, and the one potentially useful detail, the prompt-pack deliverable, 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?

For a tool with no annotations, no output schema, and no detail on grading dimensions, inputs, or results, the definition leaves the agent unable to predict what calling it will produce. A caller cannot tell if the response is a store score, a diagnostic report, or literally a text prompt to reuse elsewhere.

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 parameter with 100% schema description coverage ("Optional user query to scope the analysis"), so the schema already does the documentation work and the baseline of 3 applies. The description adds no meaning about how the query influences the grading workflow or what happens when it is omitted.

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 largely restates the tool name ("fnb store grading engine") without stating a concrete verb or result: it never says whether the tool grades a store, produces a score, or just hands back a prompt template. "Delivered as a copy-paste prompt pack with examples" describes a deliverable format rather than a capability, so an agent cannot distinguish this from siblings like fnb-store-diagnostic or restaurant-ops-diagnostic.

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?

There is no when-to-use guidance, no preconditions, and no mention of any alternative despite dozens of closely related fnb/restaurant tools in the sibling list. The only signal is a target audience ("marketing and operations leaders"), which is not an invocation condition an agent can act on.

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