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wrds

wrds

by hosseinzk
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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describe_table

Retrieve column names, data types, and available WRDS column descriptions for a specified library and table to understand dataset structure before querying.

Instructions

Show columns, types and WRDS column descriptions (where available) for a table.

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": {
      "library": "<library>",
      "table": "<table>"
    },
    "name": "describe_table"
  }
}

Input Schema

NameRequiredDescriptionDefault
tableYes
libraryYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior3/5

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. 'Show' implies a read-only metadata lookup with no side effects, and it discloses that column descriptions are returned only 'where available', but it says nothing about permissions, cost, or behavior for missing/invalid tables.

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, tightly written sentence with the key output contents front-loaded and no filler. Nothing needs trimming and nothing is buried.

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

Completeness3/5

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

The output schema exists, so return-value detail is not required, and the one-liner adequately conveys the tool's intent. However, with 0% parameter coverage and no annotations, the unresolved 'library' semantics leave a real gap for an agent trying to invoke it correctly.

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

Parameters2/5

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

Schema description coverage is 0% and neither parameter is documented. The description only implies 'table'; the required 'library' parameter is never explained, nor is the expected naming format (e.g., whether it takes a library code like 'comp').

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

Purpose4/5

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

The description gives a specific verb ('Show') and resource ('columns, types and column descriptions for a table'), which is a clear describe/schema-inspection operation. It is naturally differentiated from siblings like list_tables and query, though it never names them explicitly.

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

Usage Guidelines2/5

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

There is no guidance on when to use this versus list_tables, search_catalog, or query, nor any mention of prerequisites. Usage is only weakly implied — an agent must infer it is for inspecting a known table's schema before querying.

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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