faq-generator

Generates FAQ lists from complex medical policies or protocols. Trigger when user provides medical documents, policies, or protocols and requests FAQ generation, patient education materials, or simplified explanations.

3,891 stars

Best use case

faq-generator is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Generates FAQ lists from complex medical policies or protocols. Trigger when user provides medical documents, policies, or protocols and requests FAQ generation, patient education materials, or simplified explanations.

Teams using faq-generator should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/faq-generator/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/aipoch-ai/faq-generator/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/faq-generator/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How faq-generator Compares

Feature / Agentfaq-generatorStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Generates FAQ lists from complex medical policies or protocols. Trigger when user provides medical documents, policies, or protocols and requests FAQ generation, patient education materials, or simplified explanations.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# FAQ Generator

Creates FAQ lists from medical documents.

## Features

- Automatic Q&A generation
- Policy interpretation
- Patient-friendly language
- Structured formatting

## Parameters

| Parameter | Type | Default | Required | Description |
|-----------|------|---------|----------|-------------|
| `--input`, `-i` | string | - | Yes | Source document file path |
| `--audience`, `-a` | string | general | No | Target audience (patients, researchers, general) |
| `--output`, `-o` | string | stdout | No | Output file path |
| `--format`, `-f` | string | json | No | Output format (json, markdown, text) |

## Output Format

```json
{
  "faqs": [{"question": "", "answer": ""}],
  "topic": "string"
}
```

## Risk Assessment

| Risk Indicator | Assessment | Level |
|----------------|------------|-------|
| Code Execution | No scripts included | Low |
| Network Access | No external API calls | Low |
| File System Access | Read-only within workspace | Low |
| Instruction Tampering | Standard prompt guidelines | Low |
| Data Exposure | Input/output within session | Low |

## Security Checklist

- [ ] No hardcoded credentials or API keys
- [ ] No unauthorized file system access (../)
- [ ] No network requests to external services
- [ ] Output does not expose sensitive information
- [ ] Prompt injection protections in place

## Evaluation Criteria

### Success Metrics
- [ ] FAQ accurately represents source document content
- [ ] Language is appropriate for specified audience (patients/researchers)
- [ ] Questions cover key points of the document
- [ ] Answers are clear, concise, and medically accurate
- [ ] Format follows structured JSON schema

### Test Cases
1. **Basic FAQ Generation**: Input simple medical protocol → Output valid FAQ list
2. **Audience Adaptation**: Same input with different audiences → Appropriate tone shift
3. **Complex Document**: Input lengthy policy document → Comprehensive FAQ coverage
4. **Edge Case**: Input ambiguous content → Handles gracefully with clarifying questions

## Lifecycle Status

- **Current Stage**: Draft
- **Next Review Date**: 2026-03-06
- **Known Issues**: None
- **Planned Improvements**: 
  - Add support for multi-language output
  - Enhance medical terminology handling

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