qra
Extract Question-Reasoning-Answer pairs from text. Use --context for domain-focused extraction. Validates answers are grounded in source text.
Profile →npx skills add majiayu000/claude-skill-registry --skill qra --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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 d
- Happy Path
- Parameters
- What It Does
- When to Use
- Examples
- Environment Variables (Optional Tuning)
Extract from text file With domain focus (recommended) Preview before storing From stdin cat meeting_notes.txt | ./run.sh --scope meetings Meeting transcript Code documentation From clipboard/pipe pbpaste | ./run.sh --scope notes --dry-run
What does the qra skill do?
Extract Question-Reasoning-Answer pairs from text. Use --context for domain-focused extraction. Validates answers are grounded in source text.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill qra --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.