Save hours every week. This report analyze 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?
With no annotations, the description carries the full disclosure burden, yet it says nothing about what the tool returns, whether it reads or mutates anything, or what the operating playbook contains. The only behavioral claims ("no setup," "works in any LLM chatbot") are ambient rather than functional, so an agent still cannot predict the response.
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 two sentences, but the leading line ("Save hours every week") is pure marketing and occupies the front-loaded position where the purpose should be. The second sentence piles on promotional clauses ("battle-tested," "No setup") rather than concrete capability 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?
The tool is simple (one optional parameter, no output schema), but the description still fails to establish the core contract: what the agent gets back and what kind of report/brand input it should supply. Against a sibling set of five similarly named report tools, that omission is disqualifying rather than minor.
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% for the single optional "query" parameter, whose description already says it scopes the analysis, so the baseline is 3. The description adds nothing about how the query shapes the output or what to pass when omitting it.
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 restates the tool name ("report analyze tool") and frames the value as "a battle-tested prompt and operating playbook for restaurant/brand growth," but never states what the tool actually does — whether it analyzes a report, generates a prompt, or returns a playbook. It gives no differentiation from siblings such as report-board-tool, report-diag-tool, report-formula-tool, report-tpl-tool, or report-writer-pro.
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 usage guidance. There is no statement of when to call this tool, when not to, or which of the many report-* siblings to prefer for a given task, leaving the agent to guess.
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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