feat: add 61 new skills from VoltAgent repository

- 27 official team skills (Sentry, Trail of Bits, Expo, Hugging Face, etc.)
- 34 community skills including context engineering suite
- All skills validated and compliant with V4 quality bar
- Complete source attribution maintained

Skills added:
- Official: commit, create-pr, find-bugs, iterate-pr, culture-index, fix-review, sharp-edges, expo-deployment, upgrading-expo, hugging-face-cli, hugging-face-jobs, vercel-deploy-claimable, design-md, using-neon, n8n-*, swiftui-expert-skill, fal-*, deep-research, imagen, readme, screenshots
- Community: frontend-slides, linear-claude-skill, skill-rails-upgrade, context-*, multi-agent-patterns, tool-design, evaluation, memory-systems, terraform-skill, and more

skills/deep-research/SKILL.md

@@ -0,0 +1,114 @@
+---
+name: deep-research
+description: "Execute autonomous multi-step research using Google Gemini Deep Research Agent. Use for: market analysis, competitive landscaping, literature reviews, technical research, due diligence. Takes 2-10 minutes but produces detailed, cited reports. Costs $2-5 per task."
+source: "https://github.com/sanjay3290/ai-skills/tree/main/skills/deep-research"
+risk: safe
+---
+
+# Gemini Deep Research Skill
+
+Run autonomous research tasks that plan, search, read, and synthesize information into comprehensive reports.
+
+## When to Use This Skill
+
+Use this skill when:
+- Performing market analysis
+- Conducting competitive landscaping
+- Creating literature reviews
+- Doing technical research
+- Performing due diligence
+- Need detailed, cited research reports
+
+## Requirements
+
+- Python 3.8+
+- httpx: `pip install -r requirements.txt`
+- GEMINI_API_KEY environment variable
+
+## Setup
+
+1. Get a Gemini API key from [Google AI Studio](https://aistudio.google.com/)
+2. Set the environment variable:
+   ```bash
+   export GEMINI_API_KEY=your-api-key-here
+   ```
+   Or create a `.env` file in the skill directory.
+
+## Usage
+
+### Start a research task
+```bash
+python3 scripts/research.py --query "Research the history of Kubernetes"
+```
+
+### With structured output format
+```bash
+python3 scripts/research.py --query "Compare Python web frameworks" \
+  --format "1. Executive Summary\n2. Comparison Table\n3. Recommendations"
+```
+
+### Stream progress in real-time
+```bash
+python3 scripts/research.py --query "Analyze EV battery market" --stream
+```
+
+### Start without waiting
+```bash
+python3 scripts/research.py --query "Research topic" --no-wait
+```
+
+### Check status of running research
+```bash
+python3 scripts/research.py --status <interaction_id>
+```
+
+### Wait for completion
+```bash
+python3 scripts/research.py --wait <interaction_id>
+```
+
+### Continue from previous research
+```bash
+python3 scripts/research.py --query "Elaborate on point 2" --continue <interaction_id>
+```
+
+### List recent research
+```bash
+python3 scripts/research.py --list
+```
+
+## Output Formats
+
+- **Default**: Human-readable markdown report
+- **JSON** (`--json`): Structured data for programmatic use
+- **Raw** (`--raw`): Unprocessed API response
+
+## Cost & Time
+
+| Metric | Value |
+|--------|-------|
+| Time | 2-10 minutes per task |
+| Cost | $2-5 per task (varies by complexity) |
+| Token usage | ~250k-900k input, ~60k-80k output |
+
+## Best Use Cases
+
+- Market analysis and competitive landscaping
+- Technical literature reviews
+- Due diligence research
+- Historical research and timelines
+- Comparative analysis (frameworks, products, technologies)
+
+## Workflow
+
+1. User requests research → Run `--query "..."`
+2. Inform user of estimated time (2-10 minutes)
+3. Monitor with `--stream` or poll with `--status`
+4. Return formatted results
+5. Use `--continue` for follow-up questions
+
+## Exit Codes
+
+- **0**: Success
+- **1**: Error (API error, config issue, timeout)
+- **130**: Cancelled by user (Ctrl+C)