distill

name	distill
description	Distill PDF, URL, or text into Q&A pairs stored in memory. Use --context for domain-focused extraction.
allowed-tools	Bash, Read, WebFetch
triggers	["distill this","distill this pdf","distill this paper","extract knowledge from","remember this paper","store this research","learn from this document","ingest this pdf"]
metadata	{"short-description":"Distill content into Q&A pairs for memory"}

Distill Skill

Distill PDF, URL, or text into Q&A pairs and store in memory.

Happy Path

# Distill a PDF into memory
./run.sh --file paper.pdf --scope research

# With domain focus (recommended for better relevance)
./run.sh --file paper.pdf --scope research --context "ML researcher"

# Preview before storing
./run.sh --file paper.pdf --dry-run

# From URL
./run.sh --url https://example.com/article --scope web

Parameters

Flag	Description
--file	PDF, markdown, or text file
--url	URL to fetch and distill
--scope	Memory scope (default: research)
--context	Domain focus, e.g. "security expert"
--dry-run	Preview without storing
--json	JSON output
--sections-only	Extract sections only (no Q&A)

What It Does

1. Extract content from PDF/URL/text
2. Split into logical sections
3. Generate Q&A pairs via LLM
4. Validate answers are grounded in source
5. Store to memory via memory-agent learn

Examples

# Research paper
./run.sh --file arxiv_paper.pdf --scope research --context "ML researcher"

# Technical documentation
./run.sh --file api_docs.md --scope project --context "backend developer"

# Just extract sections (no Q&A)
./run.sh --file paper.pdf --sections-only --json

Environment Variables (Optional Tuning)

Variable	Default	Description
DISTILL_PDF_MODE	fast	PDF mode: fast, accurate, auto
DISTILL_CONCURRENCY	6	Parallel LLM requests
DISTILL_GROUNDING_THRESH	0.6	Grounding similarity threshold
DISTILL_NO_GROUNDING	-	Set to 1 to skip validation