Save hours every week. This sales board tool 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 provided, so the description carries the entire behavioral burden, yet it discloses nothing about what the tool returns, what form the 'playbook' takes, whether output is static template text or query-scoped analysis, or any cost/side effects. 'Save hours every week' and 'works in any LLM chatbot' are promissory marketing rather than 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?
Only three short sentences, but the lead position is spent on a benefit claim ('Save hours every week') rather than on what the tool does. Every sentence is promotional filler that fails to earn its place over a functional statement of purpose.
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 description that never explains the tool's mechanics, an agent cannot determine what invoking this tool will produce. For a tool sitting among hundreds of similarly named sales and restaurant siblings, this is materially incomplete.
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 'query' parameter with full schema description coverage, so the schema already explains its meaning. The description adds nothing about how the query scopes the analysis, which is acceptable given the 100% coverage baseline but provides no extra value.
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 says it is a 'sales board tool toolkit' offering a 'battle-tested prompt and operating playbook for restaurant/brand growth', which hints at advisory/prompt content but never states a concrete verb or what the tool actually does when called. It restates the tool name with marketing framing and gives no way to distinguish it from siblings such as sales-analyze-tool, sales-diag-tool, or the many fnb-* restaurant tools.
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 guidance about when to invoke this tool versus alternatives. There is no mention of prerequisite context, no exclusions, and no pointer to a sibling tool for adjacent tasks despite dozens of near-duplicate sales-* and restaurant-* options.
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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