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sktime

sktime-mcp

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by sktime

call_method

Call any native method on an instantiated sktime component for non-standard scitypes like splitters, metrics, or aligners. Provide method name and keyword arguments as a dictionary.

Instructions

Dynamically call any native method on an instantiated sktime component (e.g. 'split', 'get_alignment', 'call'). Use this tool to interact with non-standard scitypes like Splitters, Metrics, or Aligners that do not support the generic 'fit' or 'predict' endpoints. Pass 'kwargs' as a dictionary of arguments.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kwargsNoDictionary of keyword arguments to pass to the method. Pass '_dataset' or '_data_handle' as suffixes in keys to inject memory data (e.g., {'y_dataset': 'airline'}).
handle_idYesMemory handle ID of the instantiated component
method_nameYesName of the method to call (e.g. 'split')
Behavior3/5

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

No annotations provided, so description carries full burden. It mentions dynamic calling and kwargs with special suffixes, but does not disclose potential error behavior, side effects, or security implications. Adequate but not thorough.

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?

Extremely concise at two sentences, front-loaded with action and examples. Every sentence adds value without redundancy.

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?

Given the complexity of a dynamic method call tool and no output schema, the description omits return value and error handling. It covers purpose and basic usage but not operational details that could aid agent execution.

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 100%, so baseline is 3. The description adds general context but does not significantly enhance parameter understanding beyond the schema's own descriptions. No new semantics for individual parameters.

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 verb 'call', resource 'native method on instantiated sktime component', and distinguishes from siblings by specifying it's for non-standard scitypes not covered by 'fit' or 'predict'. Examples enhance clarity.

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?

Explicitly states when to use the tool (for non-standard scitypes lacking generic endpoints), though it does not explicitly mention when not to use it. The context is clear enough for correct selection.

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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