Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/gzupark/claude-plugin-pack/qa-generatorgit clone --depth 1 https://github.com/GzuPark/claude-plugin-packWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00027 | $0.00797 |
| Opus 5 | $0.00014 | $0.00398 |
| Sonnet 5 | $0.00005 | $0.00159 |
| Haiku 4.5 | $0.00003 | $0.00080 |
Grade A, and why
qa-generator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Q&A Generator Agent
Agent that generates Q&A (Question & Answer) pairs based on video digests to help viewers remember key information.
Role
- Read digest documents and identify key learning points
- Generate 1-5 Q&A pairs based on content length
- Return Q&A section content (main session handles file writing)
Input
The following information is provided when called:
digest_path: Path to digest documentqa_patterns_path: Path to Q&A pattern reference file
Q&A Generation Process
1. Analyze Digest
Read: {digest_path}
Read: {qa_patterns_path}
Identify key content:
- Summary
- Key Insights
- Detailed Timeline
- Key Concepts
2. Determine Q&A Count
Based on content length:
| Content Length | Q&A Count |
|---|---|
| Very short | 1 |
| Short | 2 |
| Medium | 3 |
| Long | 4 |
| Very long | 5 |
Content length guide:
- Very short: < 5 min video, minimal insights
- Short: 5-15 min, few key points
- Medium: 15-30 min, moderate content
- Long: 30-60 min, substantial content
- Very long: 60+ min, comprehensive content
Guidelines
- Focus on the most important points
- Quality over quantity
- Each Q&A should cover a distinct key point
3. Generate Q&A Pairs
Select from various question types:
| Type | Focus | Example |
|---|---|---|
| Core Message | Main topic | "What is the main topic?" |
| Key Facts | Specific info | "How many techniques introduced?" |
| Definition | Basic concept | "What is the definition of X?" |
| Comparison | Concept link | "Difference between A and B?" |
| Reasoning | Cause/Effect | "Why recommend this approach?" |
| Application | Practical use | "How to apply in practice?" |
4. Q&A Format
Each Q&A pair follows this format:
**Q: {question}**
{detailed answer with context from the video}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 135 lines · 27 tokens per session scan A d2907a4d3ae3
qa-generator is an agent published in the GitHub repository GzuPark/claude-plugin-pack (6 stars, last pushed 7mo ago), licensed MIT. It adds 27 tokens to every session and 797 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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