Save hours every week. This perf check 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 full burden. It adds only 'No setup, works in any LLM chatbot' and 'Save hours every week' — pure marketing with no disclosure of what the tool actually does, what it returns, whether it is read-only, or any side effects.
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?
The description is short but consists entirely of promotional filler ('Save hours every week', 'battle-tested', 'No setup'). It is not front-loaded with actionable information and every sentence is marketing rather than functional detail.
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?
Given a simple one-parameter tool with no output schema and no annotations, the description should explain the core operation and expected result. Instead, it provides only a sales pitch, leaving an agent unable to understand what invoking the tool accomplishes.
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 input schema has one optional 'query' parameter with a clear schema description ('Optional user query to scope the analysis'), and coverage is 100%. Per the baseline rule, a score of 3 is appropriate even though the description adds no parameter-specific meaning.
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 never states a specific verb or resource for the tool. 'Perf check tool toolkit' restates the name, and the rest is marketing about a 'prompt and operating playbook for restaurant/brand growth' — it does not clarify whether the tool performs a performance check, returns a prompt, or does something else, nor does it distinguish it from the many perf-* 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 guidance, no exclusions, and no mention of alternatives. The only contextual hint is 'restaurant/brand growth', which is too vague to guide selection among the numerous sibling tools.
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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