distill

Name: distill
Availability: InStock
Author: Graham

Convert PDFs, URLs, or text into memory-ready Q&A pairs.

1|Updated Nov 12, 2025

Search Tags:#pdf #qa #llm #memory #distill #text #web

Ready to run

npx skills add https://github.com/grahama1970/fetcher --skill distill-grahama1970

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: distill
Source: https://github.com/grahama1970/fetcher/tree/main/.agents/skills/distill
Command: npx skills add https://github.com/grahama1970/fetcher --skill distill-grahama1970

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Distill content from PDFs, URLs, or plain text into concise, memory-friendly Q&A pairs that can be stored and recalled on demand.

Core Features & Use Cases

Content distillation: Extracts text from PDFs, web pages, or documents and converts it into structured Q&A pairs suitable for memory.
Memory storage: Persists the generated Q&A in a memory system via the memory-agent learn workflow for quick retrieval.
Context-aware extraction: Accepts domain context (e.g., "ML researcher") to tailor the distillation for relevance.

Quick Start

Distill a PDF, URL, or text into memory with domain context to generate Q&A pairs.

Frequently Asked Questions about distill

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I distill text from a PDF into Q&A pairs for memory storage?▼

You can distill web page content into memory-ready Q&A pairs by providing the URL and an optional domain context. The system extracts the text, grounds the answers in the source material, and stores the Q&A pairs in memory.

Can I tailor extracted Q&A pairs to a specific research domain?▼

Yes, you can tailor extracted Q&A pairs by providing a domain context parameter such as "ML researcher." This context shapes the distillation process to generate memory-ready Q&A pairs relevant to your specific field.

Does the distillation process ground answers in the original source text?▼

The distillation process enforces grounding by deriving answers directly from the provided source content. It uses an LLM as needed to ensure the generated Q&A pairs accurately reflect the original PDF, web page, or text.

What is the best way to convert plain text into memory-ready Q&A pairs?▼

The best way to convert plain text into memory-ready Q&A pairs is using a distillation workflow that accepts raw text and domain context. It generates grounded Q&A pairs and persists them via a memory-agent learn workflow for quick recall.

How are distilled Q&A pairs stored for later retrieval?▼

Distilled Q&A pairs are stored in a memory system using the memory-agent learn workflow. This persistence allows the generated Q&A pairs to be quickly recalled on demand for future reference.