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Agent skill

Bdistill Knowledge Extraction

by majiayu000 in majiayu000/claude-skill-registry

Extract structured domain knowledge from AI models in-session or from local open-source models via Ollama.

MITAuto-check passedAI & LLM Engineering

Install Bdistill Knowledge Extraction

skills CLI
$ npx skills add majiayu000/claude-skill-registry --skill bdistill-knowledge-extraction -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install majiayu000/claude-skill-registry bdistill-knowledge-extraction --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ai-ml/bdistill-knowledge-extraction .claude/skills/bdistill-knowledge-extraction && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
bdistill-knowledge-extraction
GitHub stars
666
Used in
3 other repos
Token cost
~847 tokens
SKILL.md length
230 words
Files
2
Skills in repo
1,273
Repo updated
First seen
Licence
MIT

At a glance

Extract structured domain knowledge from AI models in-session or from local open-source models via Ollama.

  • Works in 3 steps: Install → Extract knowledge in-session → Search, export, compound
  • Tasks that involve LLM inference and serving
  • SKILL.md covers Overview, When to Use This Skill, How It Works and Output Format, plus 4 more sections
  • Calls ollama, pip and claude; reaches ollama.com

What it does

Bdistill Knowledge Extraction is an agent skill from majiayu000/claude-skill-registry. Extract structured domain knowledge from AI models in-session or from local open-source models via Ollama. No API key needed.

Its SKILL.md is about 850 tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `metadata.json`).

It sits in AI & LLM Engineering, covering LLM inference and serving. It works with Ollama. The repository describes itself as: Searchable Claude Code skills catalog with source-linked guides and generated registry artifacts. The licence is MIT.

When your agent uses it

  • Tasks that involve LLM inference and serving

Example prompts

  • “/bdistill-knowledge-extraction”

Requirements

  • Python 3
  • Docker

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Install
  2. Extract knowledge in-session
  3. Search, export, compound

What it can do on your machine

Read from SKILL.md and the folder at commit 2d14a69. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • ollama
    • pip
    • claude

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • ollama.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Bdistill Knowledge Extraction loads about 847 tokens when it runs. Until then it costs about 39 tokens; SKILL.md has 230 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~39
When it runs · the whole SKILL.md, loaded when a task matches
~847

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from majiayu000/claude-skill-registry at commit 2d14a69, republished under its MIT licence (© majiayu000). 230 words, ~847 tokens.

Download SKILL.mdSave it as .claude/skills/bdistill-knowledge-extraction/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
bdistill-knowledge-extraction
description
Extract structured domain knowledge from AI models in-session or from local open-source models via Ollama. No API key needed.
category
ai-research
risk
safe
source
community
date_added
2026-03-20
author
FrancyJGLisboa
tags
ai, knowledge-extraction, domain-specific, data-moat, mcp, reference-data
tools
claude, cursor, codex, copilot

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 validated knowledge entries.

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
bash
pip install bdistill
claude mcp add bdistill -- bdistill-mcp   # Claude Code
Step 2: Extract knowledge in-session
/distill medical cardiology                    # Preset domain
/distill --custom kubernetes docker helm       # Custom terms
/distill --adversarial medical                 # With adversarial validation
Step 3: Search, export, compound
bash
bdistill kb list                               # Show all domains
bdistill kb search "atrial fibrillation"       # Keyword search
bdistill kb export -d medical -f csv           # Export as spreadsheet
bdistill kb export -d medical -f markdown      # Readable knowledge document

Output Format

Structured reference JSONL — not training data:

json
{
  "question": "What causes myocardial infarction?",
  "answer": "Myocardial infarction results from acute coronary artery occlusion...",
  "domain": "medical",
  "category": "cardiology",
  "tags": ["mechanistic", "evidence-based"],
  "quality_score": 0.73,
  "confidence": 1.08,
  "validated": true,
  "source_model": "Claude Sonnet 4"
}

Tabular ML Data Generation

Generate structured training data for traditional ML models:

/schema sepsis | hr:float, bp:float, temp:float, wbc:float | risk:category[low,moderate,high,critical]

Exports as CSV ready for pandas/sklearn. Each row tracks source_model for cross-model analysis.

Local Model Extraction (Ollama)

For open-source models running locally:

bash
# Install Ollama from https://ollama.com
ollama serve
ollama pull qwen3:4b

bdistill extract --domain medical --model qwen3:4b

Security & Safety Notes

  • In-session extraction uses your existing subscription — no additional API keys
  • Local extraction runs entirely on your machine via Ollama
  • No data is sent to external services
  • Output is reference data, not LLM training format
  • @bdistill-behavioral-xray - X-ray a model's behavioral patterns

© majiayu000, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/ai-ml/bdistill-knowledge-extraction of majiayu000/claude-skill-registry.

  • SKILL.md
  • metadata.json

Open the folder on GitHubat commit 2d14a69

Used in 3 other repositories

We found 12 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in majiayu000/claude-skill-registry, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Bdistill Knowledge Extraction next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Bdistill Knowledge Extraction compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Bdistill Knowledge Extraction this skillmajiayu000/claude-skill-registry6663 repos~847Automated safety check: PassMIT
Subwave LLM Benchperminder-klair/subwave1.4k—~2.4kAutomated safety check: NotesMIT
Pii Safe Documentsdanyuchn/pii-guard249—~2.7kAutomated safety check: PassMIT
Visiongridaco/grida2.7k—~1.5kAutomated safety check: PassApache-2.0
Domodomo Local AI Maintenancedarknecrocities/DomoDomo---All-in-one-Tool239—~17kAutomated safety check: PassNone
Cc Ollamamathruffian-dot/claude-code-lazy-packs254—~118Automated safety check: PassMIT

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Works with

Categories

Questions about Bdistill Knowledge Extraction

What does Bdistill Knowledge Extraction do?

Extract structured domain knowledge from AI models in-session or from local open-source models via Ollama. Bdistill Knowledge Extraction is an agent skill from majiayu000/claude-skill-registry. Extract structured domain knowledge from AI models in-session or from local open-source models via Ollama.

When should I use Bdistill Knowledge Extraction?

Bdistill Knowledge Extraction fits situations like: tasks that involve LLM inference and serving.

How do I install Bdistill Knowledge Extraction in Claude Code?

Run `npx skills add majiayu000/claude-skill-registry --skill bdistill-knowledge-extraction -a claude-code`. Or copy the skill folder (skills/ai-ml/bdistill-knowledge-extraction in majiayu000/claude-skill-registry) into .claude/skills/bdistill-knowledge-extraction in your project. Claude Code loads it when a task matches its description.

How do I install Bdistill Knowledge Extraction in Codex?

Run `npx skills add majiayu000/claude-skill-registry --skill bdistill-knowledge-extraction -a codex`. Or copy the skill folder (skills/ai-ml/bdistill-knowledge-extraction in majiayu000/claude-skill-registry) into .agents/skills/bdistill-knowledge-extraction in your project. Codex loads it when a task matches its description.

Can I use Bdistill Knowledge Extraction in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add majiayu000/claude-skill-registry --skill bdistill-knowledge-extraction -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/bdistill-knowledge-extraction, .gemini/skills/bdistill-knowledge-extraction, .github/skills/bdistill-knowledge-extraction and .opencode/skills/bdistill-knowledge-extraction in your project.

What does Bdistill Knowledge Extraction need to run?

Going by SKILL.md and its folder, Bdistill Knowledge Extraction needs the command-line tools its instructions call (ollama, pip and claude). Our summary lists: Python 3; Docker.

Does Bdistill Knowledge Extraction access the network?

SKILL.md names 1 domain. In commands or code: ollama.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Bdistill Knowledge Extraction safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Bdistill Knowledge Extraction use?

Bdistill Knowledge Extraction is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Bdistill Knowledge Extraction use?

About 847 tokens (SKILL.md is roughly 3.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Bdistill Knowledge Extraction?

Skills that share tags, products or a category with Bdistill Knowledge Extraction: Subwave LLM Bench (perminder-klair/subwave, 1.4k stars), Pii Safe Documents (danyuchn/pii-guard, 249 stars), Vision (gridaco/grida, 2.7k stars) and Domodomo Local AI Maintenance (darknecrocities/DomoDomo---All-in-one-Tool, 239 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Bdistill Knowledge Extraction?

majiayu000 (a GitHub user) maintains it in majiayu000/claude-skill-registry, which has 666 GitHub stars. The repository holds 1,273 skills in this directory. The repository was last updated on October 7, 2026.

Source: majiayu000/claude-skill-registry on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.