Save hours every week. This meeting audit 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 offers only sales claims ('save hours every week', 'no setup, works in any LLM chatbot') and says nothing about what the tool actually does, what it returns, or any constraints.
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 all three are marketing filler with no operational content. Brevity here reflects under-specification rather than conciseness.
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?
The tool has one parameter and no annotations or output schema, so the description must supply the entire behavior model. It supplies none, leaving an agent unable to tell what the tool does or how it differs from dozens of meeting-related siblings.
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 coverage is 100%, so the baseline would be 3, but the description never mentions the 'query' parameter or how it scopes the analysis. Worse, the growth-playbook framing contradicts the schema's implication of query-scoped meeting analysis.
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 name says 'meeting audit' but the description describes a 'prompt and operating playbook for restaurant/brand growth,' which is a different resource than a meeting audit. It restates the tool name ('meeting audit tool toolkit') rather than explaining the operation, and the growth-playbook framing actively muddies what the tool returns.
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 when-to-use, when-not-to-use, or alternative is named. With hundreds of siblings such as meeting-check-tool, meeting-summary-tool, and meeting-minutes, no routing guidance at all is a serious gap.
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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