Extract Question-Reasoning-Answer pairs from text. Use --context for domain-focused extraction. Validates answers are grounded in source text.
Scanned 9/2/2026
Install to Claude Code
npx -y skills add majiayu000/claude-skill-registry --skill qra --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: qra
description: >
Extract Question-Reasoning-Answer pairs from text.
Use --context for domain-focused extraction.
Validates answers are grounded in source text.
allowed-tools: Bash, Read
triggers:
- extract QRA
- extract Q&A
- extract knowledge
- create Q&A pairs
- knowledge extraction
- generate questions from
metadata:
short-description: Extract grounded Q&A pairs from text
---
# QRA Skill
Extract Question-Reasoning-Answer pairs from text and store in memory.
## Happy Path
```bash
# Extract from text file
./run.sh --file document.md --scope research
# With domain focus (recommended)
./run.sh --file notes.txt --scope project --context "security expert"
# Preview before storing
./run.sh --file transcript.txt --dry-run
# From stdin
cat meeting_notes.txt | ./run.sh --scope meetings
```
## Parameters
| Flag | Description |
|------|-------------|
| `--file` | Text or markdown file |
| `--text` | Raw text content |
| `--scope` | Memory scope (default: research) |
| `--context` | Domain focus, e.g. "ML researcher" |
| `--dry-run` | Preview without storing |
| `--json` | JSON output |
## What It Does
1. **Split** text into logical sections
2. **Extract** Q&A pairs via LLM (parallel batch)
3. **Validate** answers are grounded in source
4. **Store** to memory via `memory-agent learn`
## When to Use
- Text content (not PDFs - use `distill` for PDFs)
- Meeting transcripts
- Code documentation
- Notes and summaries
- Any plain text you want to remember
## Examples
```bash
# Meeting transcript
./run.sh --file meeting.txt --scope team --context "project manager"
# Code documentation
./run.sh --file README.md --scope code --context "Python developer"
# From clipboard/pipe
pbpaste | ./run.sh --scope notes --dry-run
```
## Environment Variables (Optional Tuning)
| Variable | Default | Description |
|----------|---------|-------------|
| `QRA_CONCURRENCY` | 6 | Parallel LLM requests |
| `QRA_GROUNDING_THRESH` | 0.6 | Grounding similarity threshold |
| `QRA_NO_GROUNDING` | - | Set to 1 to skip validation |
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