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

With no annotations present, the description carries the full behavioral burden, yet it discloses nothing about what the tool actually returns (a prompt? a playbook document? a template?), how the optional query changes output, or whether anything is persisted. "Save hours every week" is advertising copy, not behavioral disclosure.

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?

It is short, but the front-loaded sentence ("Save hours every week") is pure marketing with zero informational value for tool selection, and the second sentence repeats the name rather than stating function. Brevity without an informative lead does not earn the space.

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?

No output schema and no annotations means the description must explain the return shape and usage context, and it does neither. For a toolbox-style tool whose output could be a prompt, a playbook, or a template set, an agent has no basis to decide what it will receive or whether to call this over siblings.

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% and there is a single optional `query` parameter already documented in the schema. The description adds no meaning about how scoping the analysis behaves, so the baseline of 3 applies when structured data does the work.

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 supervision toolbox toolkit") and layers on marketing claims. It does hint at content type ("a battle-tested prompt and operating playbook for restaurant/brand growth"), but names no concrete verb or action, and does not distinguish it from the many adjacent fnb siblings such as fnb-store-diagnostic, brand-fnb-playbook, 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?

"No setup, works in any LLM chatbot" is a portability claim, not when-to-use guidance. There is no statement of the scenario this tool suits, no exclusions, and no mention of any of the dozens of fnb alternatives an agent could pick instead.

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