Save hours every week. This gzh sop kit 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 exist, so the description carries the full behavioral burden. It only asserts 'no setup' and 'works in any LLM chatbot', saying nothing about what the tool actually returns (a prompt template? a full playbook?), whether it is read-only, or how the optional query affects output.
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 with no bloat, but the front-loaded line is a benefit slogan rather than the function, pushing the only substantive phrase ('prompt and operating playbook for restaurant/brand growth') into the middle.
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?
There is no output schema, so the description should explain the shape of the returned playbook and what the query does. Instead it delivers marketing copy, leaving an agent unable to predict the response or decide between this and the many parallel kit tools.
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 the single optional 'query' parameter is documented in the schema as scoping the analysis. The description adds no additional meaning about what the query scopes or how it shapes the returned playbook, so 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?
"This gzh sop kit toolkit gives you a battle-tested prompt and operating playbook" largely restates the tool name and is wrapped in marketing language; 'gzh' is never expanded and no concrete verb says what the call produces. It offers no differentiation from the many adjacent siblings (gzh-template-kit, gzh-checklist-kit, gzh-guide-kit, zh-sop-kit, xhs-sop-kit), so an agent cannot tell which kit to pick.
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?
"Save hours every week" and "No setup, works in any LLM chatbot" are sales claims, not guidance. There is no statement of when to invoke this versus the other gzh-*-kit or *-sop-kit tools, and no preconditions or exclusions are given.
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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