Save hours every week. This geo schema generator 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 behavioral burden, and it discloses nothing about what happens on invocation, what is returned, permissions, or cost. "No setup, works in any LLM chatbot" is marketing filler rather than behavioral information.
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 three short sentences, but the opening "Save hours every week" and "No setup, works in any LLM chatbot" are pure advertising that consume space without informing the caller. There is no front-loaded statement of operation.
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?
With no annotations, no output schema, and no explanation of return values or generated content, an agent has no basis for deciding what it will get back. The definition is effectively a sales blurb rather than a tool specification.
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?
With a single optional parameter at 100% schema description coverage, the schema already explains the query field, so the baseline of 3 applies. The description adds no meaning about how the query scopes the 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 description mostly restates the tool name ("geo schema generator toolkit") and never states the concrete operation, input consumed, or artifact produced. Phrases like "battle-tested prompt and operating playbook" gesture at deliverables but an agent cannot tell what calling this actually yields.
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 and no differentiation from the many GEO siblings (geo-audit-tool, geo-content-factory, geo-knowledge-graph, brand-geo-fetch). The only context cue is "restaurant/brand growth," which hints at domain but not at the selection decision.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.