Save hours every week. This ecom detail optimizer 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 supplied, so the description carries the full behavioral burden, and it discloses almost nothing: it hints the tool returns a prompt/playbook rather than performing an analysis, but never states what the output is, whether the 'query' changes anything, or what happens with no query. Marketing claims ('save hours every week') occupy the space that behavioral disclosure should fill.
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?
It is short, but every sentence is promotional filler ('Save hours every week', 'battle-tested', 'No setup') rather than front-loaded substance. Nothing in the two sentences earns its place as tool documentation.
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, but with no annotations and no output schema the description must explain what actually comes back — a prompt template, a rewritten detail page, a checklist? It does not, and it leaves the relationship between the optional query and the returned artifact entirely undefined.
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% for the single optional 'query' parameter, so the schema already explains it ('Optional user query to scope the analysis'), and the baseline of 3 applies. The description adds no meaning about how the query scopes the output or what an omitted query produces.
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 title ('ecom detail optimizer toolkit') and adds only promotional framing: 'a battle-tested prompt and operating playbook for restaurant/brand growth.' It never says what the tool actually does to an e-commerce detail page, and the 'restaurant/brand growth' scope actively muddies an e-commerce-detail tool. No distinction from siblings such as ecom-detail-page or ecom-copy-pro is offered.
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 prerequisites, and no mention of when a sibling like ecom-copy-pro or ecom-detail-page should be chosen instead. 'No setup, works in any LLM chatbot' describes deployment, not invocation context, so an agent gets no routing signal from this text.
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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