langextract
langextract — LLM-Powered Structured Information Extraction
Extract structured data from unstructured text with character-level provenance. Every extracted entity traces back to exact character offsets in the source document.
When to use this skill
- Extracting entities, relationships, or facts from unstructured text
- Processing clinical notes, legal documents, research papers, or reports
- Building NLP pipelines that need citation-level traceability (not just extracted values)
- Long-document extraction (chunking + parallel workers + multi-pass for recall)
- Replacing fragile regex/rule-based extraction with LLM-driven schema enforcement
- Generating interactive HTML visualizations of annotated text
1. Installation
More from akillness/oh-my-gods
deepagents
>
19agent-workflow
>
19data-analysis
>
16omg
OMG — Integrated AI agent orchestration skill. Plan with ralph+plannotator, execute with team/bmad, verify browser behavior with agent-browser, apply UI feedback with agentation(annotate), auto-cleanup worktrees after completion. Supports Claude, Codex, Gemini CLI, and OpenCode. Install: ralph, omc, omx, ohmg, bmad, plannotator, agent-browser, agentation.
16frontend-design-system
Produce production-grade UI designs using clear design tokens, layout rules, motion guidance, and accessibility checks for consistent, scalable frontend development.
15omc
oh-my-claudecode — Teams-first multi-agent orchestration layer for Claude Code. 32 specialized agents, smart model routing, persistent execution loops, and real-time HUD visibility. Zero learning curve.
15