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

With no annotations, the description carries the full behavioral burden and largely fails it. It hints that the tool delivers a prompt/playbook artifact rather than performing analysis, but discloses nothing about output format, whether any external data is used, or what the optional query actually influences.

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?

Three short sentences, but they are spent on benefit claims ('Save hours every week', 'No setup') instead of function. The text is front-loaded with marketing rather than the tool's purpose, so it is brief but not efficient.

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 essentially no annotations, no output schema, and a vague prompt-delivery behavior, the description should explain what comes back and how to use it. Instead it leaves the agent guessing whether this is a generator, a knowledge base, or an analysis 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?

Schema description coverage is 100% — the single optional 'query' parameter is documented in the schema — so the baseline of 3 applies. The description adds no meaning about what the query scopes 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 mostly restates the tool name ('fnb site selector toolkit') and wraps it in marketing claims ('battle-tested prompt and operating playbook'). It never states the actual operation — e.g. that it produces guidance for choosing a restaurant location — and does not differentiate from close siblings such as store-site-selector, sanhao-store-site-selector, or store-area-insight.

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 sales claim, not usage guidance. There is no statement of when to invoke this tool, when not to, or which sibling to pick for adjacent site/location tasks, despite dozens of similar tools in the list.

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