List all lookup tables with their IDs, names, and schemas to quickly assess data structures for recipe automation.
List lookup tables (id, name, schema).
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "list_lookup_tables"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.2.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral disclosure burden. It at least implies a read-only listing operation and specifies the returned fields, but it does not mention pagination, authorization requirements, or error behavior. This is minimal but acceptable for a simple no-parameter tool.
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?
The description is a single concise sentence with no filler. It front-loads the action and resource, making it easy to parse.
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 simple no-parameter tool with no output schema, the description is reasonably complete: it states the operation and expected fields. However, it lacks explicit use-case context or exclusions relative to sibling tools, so it is adequate but not rich.
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 tool has zero parameters, and the schema is empty, so there are no parameter semantics to explain. The baseline for 0 params is 4, and the description usefully adds the output field list (id, name, schema).
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?
Description uses a specific verb ('List') and resource ('lookup tables'), and it clearly states the output fields (id, name, schema). It does not explicitly distinguish this from sibling list_data_tables, but the tool name and field list make the purpose clear.
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?
The description gives no guidance on when to use this tool versus alternatives like list_data_tables or query_lookup_table. It only states what the tool does, leaving the agent to infer appropriate usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.