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clearskies-py

clearskies MCP Server

list_available_columns

Discover all clearskies column types with brief descriptions to guide your data model design.

Instructions

List all available clearskies column types with a short description of each.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries the full burden of disclosing behavior. It indicates the tool lists all column types and includes short descriptions, which is useful. However, it does not explicitly state that the operation is read-only, non-destructive, or whether any authentication is required. For a simple listing tool, the behavior is largely implied but not fully disclosed.

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 a single, well-structured sentence that leads with the action and resource, followed by the valuable detail about short descriptions. No unnecessary words or repetition.

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

Completeness4/5

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

For a simple listing tool with no parameters and an output schema present, the description is nearly complete. It covers what is listed and the nature of the output (short descriptions). It could be slightly more explicit about the purpose (e.g., for use in model creation), but it is sufficient for an agent to select and invoke the tool correctly.

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 does not need to explain parameter semantics. It correctly focuses on the tool's purpose and output quality (short descriptions).

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 clearly states the tool's function: 'List all available clearskies column types with a short description of each.' It uses a specific verb ('list'), identifies the resource ('clearskies column types'), and differentiates itself from sibling list_available_* tools by specifying 'column types'.

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

Usage Guidelines4/5

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

The description implies the tool is used to discover available column types, but it does not explicitly state when to use it versus alternatives or mention any exclusions. The context is clear, however, and the sibling tool names reinforce the intended use case for column types.

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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