Distill PDF, URL, or text into Q&A pairs stored in memory. Use --context for domain-focused extraction.
Scanned 9/2/2026
Install to Claude Code
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---
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
```bash
# 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
```bash
# 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 |
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