Extract atomic claims with provenance from unstructured text sources.
npx skills add https://github.com/MantisWare/BizForge --skill reduce-mantisware
Please help me install this Agent Skill. Skill: reduce Source: https://github.com/MantisWare/BizForge/tree/main/library/skills/processing/reduce Command: npx skills add https://github.com/MantisWare/BizForge --skill reduce-mantisware
Extract atomic, provenance-rich claims from unstructured source material to enable reliable reuse and audit trails.
Reduce a document by running /reduce path/to/source.md to generate atomic claims with provenance.
High-intent search queries and answers about installing and using this skill.
Parsing meeting transcripts into structured data with provenance involves decomposing the text into atomic claims. Each claim is enriched with source provenance, confidence scores, and topic tags to ensure reliable audit trails.
Yes, you can convert raw articles into YAML-frontmatter compliant structured claims. The extraction pipeline applies segmentation, classification, deduplication, and enrichment to transform unstructured source material into reusable, atomic data.
Yes, the claim extraction process automatically tags outputs with confidence and topics. During the extraction and classification stages, the pipeline enriches atomic claims with provenance metadata, confidence scores, and relevant topic tags.
To deduplicate extracted claims from multiple documents, the deterministic pipeline includes a deduplication stage after extraction and classification. This ensures the final structured output contains only unique, atomic claims with accurate provenance.
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