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AI-ML-Lab-MCP

AI-ML-Lab-MCP

by SyedHassan904
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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Drop Column

drop_column

Removes a named column from a dataset by dataset ID and returns the dataset ID with the deleted column name, helping clean or reshape data before analysis.

Instructions

Drop a column from the dataset. Args: dataset_id (str): ID of the dataset. column_name (str): Name of the column to remove. Returns: dict: Dataset ID and deleted column name.

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": {
      "dataset_id": "<dataset_id>",
      "column_name": "<column_name>"
    },
    "name": "drop_column"
  }
}

Input Schema

NameRequiredDescriptionDefault
dataset_idYes
column_nameYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries full behavioral burden. It implies a destructive, likely irreversible mutation but never says so, nor does it state what happens if the column is missing or whether the operation can be undone. It does add a return shape ('Dataset ID and deleted column name'), which is the only behavioral detail present.

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

Conciseness4/5

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

The purpose is front-loaded in the first sentence, followed by a compact Args/Returns block. No filler or redundancy; the structure is efficient for a two-parameter tool.

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?

For a simple two-parameter mutation, the description covers purpose, both parameters, and the return value. It nonetheless omits the behavioral context a destructive operation needs, such as irreversibility and failure modes, which matters given the absence of annotations and output schema.

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

Parameters3/5

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

Schema coverage is 0%, so the description must compensate by documenting parameters. The Args block does name both parameters and describe their meaning ('ID of the dataset', 'Name of the column to remove'), which is adequate but adds no format, syntax, or constraint details beyond restating intent.

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 states a specific verb and resource: 'Drop a column from the dataset.' An agent immediately understands the mutation. It does not, however, distinguish itself from siblings like rename_column or drop_missing, leaving differentiation implicit.

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 alternatives such as drop_missing, nor any prerequisite or exclusion. The agent must infer usage entirely from the tool name and the single declarative sentence.

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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