Agent skill · research science · sickn33
bdistill-knowledge-extraction
Extract structured domain knowledge from AI models in-session or from local open-source models via Ollama. No API key needed.
Why this skill is useful
Adds executable commands for structured knowledge extraction and validation from AI models, enhancing data generation capabilities.
What it needs
Requires bdistill, claude installed locally. About 2k tokens when loaded. Last updated 2026-08-07. 44,571 stars on the source repository.
What this skill does
Knowledge Extraction Extract structured, quality-scored domain knowledge from any AI model — in-session from closed models (no API key) or locally from open-source models via Ollama. Overview bdistill turns your AI subscription sessions into a compounding knowledge base. The agent answers targeted domain questions, bdistill structures and quality-scores the responses, and the output accumulates into a searchable, exportable reference dataset. Adversarial mode challenges the agent's claims — forcing evidence, corrections, and acknowledged limitations — producing model-generated candidates for independent source review; adversarial self-correction is not external validation. When to Use This Skill Use when you need structured reference data on any domain (medical, legal, finance, cybersecurity) Use when building lookup tables, Q&A datasets, or research corpora Use when generating training data for traditional ML models (regression, classification — NOT competing LLMs) Use when you want cross-model comparison on domain knowledge How It Works Step 1: Install Step 2: Extract knowledge in-session Step 3: Search, export, compound Output Format Structured reference JSONL — not training data: The numeric scores are illustrative, uncalibrated metadata; independent source verification is absent in this example. Tabular ML Data Generation Generate structured training data for traditional ML models: Exports as CSV ready for pandas/sklearn. Each row tracks sourcemodel for cross-model analysis. Local Model Extraction (Ollama) For open-source models running locally: Security & Safety Notes In-session extraction uses your existing subscription — no additional API keys Local extraction runs entirely on your machine via Ollama In-session extraction uses the host provider and its data policy; it is not offline. A genuinely local Ollama endpoint keeps inference local, but downloading models/installing packages uses the network. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills sickn33/bdistill-knowledge-extraction--0ad46f