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shop-mcp

shop-mcp

by stalexsm
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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describe_table

Describe a table's columns, types, nullability, primary keys, and foreign-key relationships. Use after listing tables to understand the schema before writing SQL.

Instructions

Describe the structure of one table: columns with name, type, nullable and primary_key flags, plus foreign-key relationships such as 'orders.customer_id -> customers.id'. Use this after list_tables to understand the schema before writing SQL. Pass a table name that was returned by list_tables; unknown names produce a clear error.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "table_name": "<table_name>"
    },
    "name": "describe_table"
  }
}

Input Schema

NameRequiredDescriptionDefault
table_nameYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.8/5.0
Behavior4/5

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

Since annotations are absent, the description carries full burden. It discloses the return content (columns, flags, foreign keys) and error behavior for invalid input. While it doesn't explicitly state it is read-only, the non-destructive nature is strongly implied by 'describe' and the absence of any mutating language. It could have been 5 if it explicitly said 'performs no data modification', but the current disclosure is sufficient for safe invocation.

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?

The description is three concise sentences with zero filler: the first states the purpose and output, the second gives usage context, and the third constrains input and defines error behavior. It is front-loaded with the most critical information and every sentence earns its place.

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 simple tool with one parameter and no output schema, the description is complete: it covers what it does, when to use it, how to choose the parameter, and error handling. An agent has everything needed to call it correctly without additional inference. No behavioral annotations exist, but the description compensates fully for their absence.

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

Parameters5/5

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

Schema coverage is 0% and the only parameter has no description beyond its title, so the description adds significant value by explaining that the table_name must come from list_tables and that unknown names cause an error. This goes beyond the schema and directly helps the agent select a valid value, making the parameter's semantics fully clear.

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 explicitly states the verb 'describe' and the resource 'structure of one table', then lists the exact components (columns with flags, foreign keys). It clearly distinguishes itself from siblings by positioning it as the follow-up to list_tables and a prerequisite for writing SQL, while read_query is for actual data retrieval.

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

Usage Guidelines5/5

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

It gives explicit when-to-use context ('Use this after list_tables to understand the schema before writing SQL') and even instructs that the table name must come from list_tables. It also preempts misuse by stating unknown names produce a clear error, leaving no ambiguity about prerequisites or error handling.

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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