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alpha-mcp

alpha-mcp

by rsc-dev
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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list_tables

List queryable tables with primary keys, columns, and row counts to support read-only investing data queries.

Instructions

List queryable tables with their primary key, columns and row counts.

Tool call template

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_tables"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the behavioral burden. It clearly conveys a read-only metadata listing operation and specifies what information is returned. It does not explicitly mention side-effect freedom, but 'list' strongly implies a non-mutating operation and no hidden destructive behavior is suggested.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single, focused sentence that leads with the action and resource, then lists the specific output fields. Every word earns its place with no redundancy or irrelevant detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter, read-only list operation with an output schema available, the description is fully sufficient. The agent knows exactly what the tool does, what it returns, and that the call requires no arguments. Nothing essential is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the baseline is 4. The description adds no parameter detail because none exists; the schema already fully covers the argument surface. No further parameter semantics are needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('List'), a clear resource ('queryable tables'), and defines the exact return contents (primary key, columns, row counts). It clearly distinguishes itself from sibling tools like list_materials by focusing on tables rather than materials.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies its use case: call it when you need an inventory of available tables and their schema details. However, it does not explicitly state when to prefer this over alternatives or provide exclusions, leaving some inference to the agent.

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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