fix: detect forecaster-chain as invalid in sequential pipeline validation

[kpal002]

Reference Issues/PRs

Fixes #445.

What does this implement/fix? Explain your changes.

Root cause: COMPOSITION_RULES contains an ENSEMBLE rule (forecasting → forecasting, position="any") which matched the NaiveForecaster → ExponentialSmoothing pair during sequential pipeline validation. Because an applicable rule was found, the explicit forecaster-chain error check in _check_pair_compatibility was never reached, causing the validator to return valid=True.

Fix in src/sktime_mcp/composition/validator.py:

1. Added an early-return guard in _check_pair_compatibility for forecasting → forecasting pairs before the rule lookup. Two forecasters in a sequential pipeline are always invalid — ENSEMBLE composition is parallel, not sequential.

2. Added and rule.composition_type != CompositionType.ENSEMBLE to the rule-matching condition to make it explicit that ENSEMBLE-type rules should not be used to approve sequential pipeline pairs.

Result: validate_pipeline(["NaiveForecaster", "ExponentialSmoothing"]) now correctly returns valid=False with the error:

Cannot chain forecasters 'NaiveForecaster' → 'ExponentialSmoothing' directly. Use an ensemble or multiplexer instead.

This matches the ❌ icon and # Invalid pipeline: Forecaster -> Forecaster comment in examples/01_forecasting_workflow.py Step 5.

Does your contribution introduce a new dependency? If yes, which one?

No.

What should a reviewer concentrate their feedback on?

• The early-return guard in _check_pair_compatibility (lines 262–271) — confirm that sequential forecaster chaining should always be invalid with no exceptions.
• The CompositionType.ENSEMBLE filter in the rule lookup — confirm that ENSEMBLE rules should never apply in a sequential pipeline context.

Any other comments?

No new dependencies. No API changes. The fix is purely internal to _check_pair_compatibility.

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