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clearskies-py

clearskies MCP Server

explain_v1_v2_difference

Explains how specific clearskies concepts changed between versions 1 and 2, covering models, handlers, DI, columns, application, backend, and type hints.

Instructions

Explain how a specific concept changed between v1 and v2.

Args:
    concept: The concept to explain. Options:
        - 'model': Model definition changes
        - 'handler': Handler → Endpoint changes
        - 'di': Dependency injection changes
        - 'columns': Column definition changes
        - 'application': Application → Context changes
        - 'backend': Backend configuration changes
        - 'type_hints': Type hint requirements

Returns:
    Detailed explanation of the changes

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
conceptYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses the return type ('Detailed explanation of the changes') but does not explicitly state side-effect-free behavior, prerequisites, or whether it analyzes a project. The verb 'explain' implies a non-mutating read operation, but this is not made explicit.

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 well-structured: a one-sentence purpose, a clear 'Args' section with bullet-like options, and a 'Returns' section. Every sentence contributes vital information, and the format is immediately scannable.

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 tool with one parameter and an output schema (not detailed here), the description adequately covers purpose, parameter semantics, and return value. It does not mention when to use it relative to sibling migration tools, which is a minor gap but not critical given the simplicity and clear scope.

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?

The input schema only defines 'concept' as a string with no description or enum. The tool description compensates fully by listing all allowed values and explaining what each represents (e.g., 'model: Model definition changes'). This adds substantial meaning beyond the schema, meeting the 0% schema coverage gap.

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 purpose: 'Explain how a specific concept changed between v1 and v2.' It uses a specific verb ('explain'), identifies the resource (concept differences between versions), and distinguishes itself from siblings by focusing on version comparisons. The enumerated concept options further clarify the scope.

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 usage context (understanding version changes) but does not explicitly state when to use this tool over alternatives like 'explain_concept' or other migration tools. There are no explicit 'when not to use' or alternative tool references, leaving the agent to infer based on the tool name and sibling list.

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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