Save hours every week. This sanhao store site selector toolkit gives you a battle-tested prompt and operating playbook for restaurant/brand growth. No setup, works in any LLM chatbot.
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | Optional user query to scope the analysis. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are supplied, so the description carries the full burden, yet it discloses almost nothing behavioral: not whether the tool computes, retrieves, or just returns a prompt template, not what the response contains, and not any limits or prerequisites. The only concrete claim, 'No setup, works in any LLM chatbot', describes deployment portability rather than tool behavior.
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 opening sentence ('Save hours every week') is pure advertising and the rest is generic promotional filler ('battle-tested', 'No setup'). Nothing is front-loaded about capability, so the brevity reflects under-specification rather than efficiency.
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 a single opaque param, the description is the only source of truth — and it does not say what the tool returns, what inputs help, or what a site-selection result looks like. For a domain tool competing against numerous near-duplicate siblings, this is insufficient to invoke correctly.
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?
The tool has a single optional parameter whose schema description coverage is 100%, so the schema already documents it. The description says nothing about the 'query' parameter, but with full coverage and only one optional param, the baseline of 3 applies.
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 ('sanhao store site selector toolkit') and pads it with marketing framing ('battle-tested prompt and operating playbook for restaurant/brand growth'). It never states a concrete action or artifact — no verb like 'evaluate', 'score', or 'generate a site assessment' — so an agent cannot tell what the tool actually produces or how it differs from the many nearby site/store/F&B siblings.
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 or when-not-to-use guidance at all. Given siblings such as fnb-site-selector, store-site-selector, store-area-insight, sanhao-fnb-roi-gate, and restaurant-newstore-launch, the description offers nothing to disambiguate selection; 'restaurant/brand growth' is far too broad to route on.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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