Save hours every week. This compete gen 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 supplied, so the description carries the full burden. Instead of disclosing what the tool generates, whether the output is a prompt vs. an analysis, whether it requires a brand or restaurant name, or what the response looks like, it offers benefit claims. The phrase 'prompt and operating playbook' even muddies what the returned artifact actually is.
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 the first sentence is pure sales copy and the opening does not front-load what the tool does. Every sentence is a benefit statement rather than specification, so the brevity is wasted rather than efficient.
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?
For a tool sitting inside a dense family of ir-compete-* siblings, an agent gets nothing to decide selection, nothing about inputs, and nothing about the return value (there is no output schema to compensate). The definition is not complete enough to call the tool confidently.
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 single optional 'query' parameter is fully documented in the schema, but the description never mentions it or explains how a query scopes the analysis. No meaning is added beyond the schema, and the reader cannot tell whether omitting it is normal or degrades the output.
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 name ('compete gen tool toolkit') and adds only marketing claims about saving hours and being a 'prompt and operating playbook.' It never states a concrete verb-and-resource such as 'generates a competitor analysis for a restaurant brand,' and it draws no line against ir-compete-check-tool or ir-compete-tpl-tool, which are its closest 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, when-not-to-use, or prerequisite information. The only usage-adjacent sentence ('No setup, works in any LLM chatbot') is about convenience, not about when this tool is the right choice over the check or tpl variants in the same family.
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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