Implement SDK and MCP methods for Classify#242
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dschwarz26 merged 6 commits intomainfrom Feb 27, 2026
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- Add classify() and classify_async() to SDK ops.py - Add ClassifyInput model to MCP models.py - Add everyrow_classify MCP tool to tools.py - Add classify entry to manifest.json - Add docs/reference/CLASSIFY.md and update docs/api.md - Add integration test for classify Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Update all documentation, MCP server README, skill reference, and manifest to include classify and forecast alongside existing operations. Rewrite CLASSIFY.md reference with real GICS sector example. Update tool description to describe research scaling rather than implementation phases. Point Classifiers link in README to CLASSIFY instead of SCREEN and replace screen code example with classify. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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| async def classify( | ||
| task: str, | ||
| categories: list[str], | ||
| input: DataFrame | UUID | TableResult, | ||
| classification_field: str = "classification", | ||
| include_reasoning: bool = False, | ||
| session: Session | None = None, | ||
| ) -> TableResult: | ||
| """Classify each row of a table into one of the provided categories. |
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Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Doesn't sunset Screen yet, should make sure everything is healthy for a bit first.