List all data tables in your workspace.
Returns table metadata including id, name, slug, and creation date. Use a table ID with other table_* tools to query or modify data.
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": "table_list"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false, so safety and scope are covered. The description usefully adds that the result is table metadata (id, name, slug, creation date), but says nothing about ordering, pagination, or result size for a list 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?
Three short sentences with zero filler: the operation is front-loaded, the return shape follows, and the follow-on usage closes. Every sentence earns its place.
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 parameters and no output schema, the description's enumeration of returned fields carries useful weight that structured fields do not. It remains slightly incomplete on result volume and ordering behavior for an unbounded list call.
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 takes zero parameters, so the baseline of 4 applies; there are no parameter meanings left undocumented. The description correctly emphasizes that the returned id is the key consumed by other table_* tools.
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?
Uses a specific verb plus resource ("List all data tables in your workspace") and scopes it to the workspace, so an agent can distinguish it from table_query or table_schema. It does not explicitly name a sibling it is not, so it falls short of a 5.
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 third sentence implies usage as a discovery step ("Use a table ID with other table_* tools to query or modify data"), which is useful implied guidance. However, it never says when to prefer this over dataset_list or datastore_list, and offers no explicit exclusions.
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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