moatmri
moatmri is an productivity AI skill with a core value of Analyze AI disruption pressure across a business, map competitive exposure, and produce a 90-day defensive action plan. It
helps developers solve real-world problems in the productivity domain, boosting
efficiency, automating repetitive tasks, and optimizing workflows.
Analyze AI disruption pressure across a business, map competitive exposure, and produce a 90-day defensive action plan.
mkdir -p ./skills/moatmri && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/moatmri/SKILL.md -o ./skills/moatmri/SKILL.mdRun in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
Analyze AI disruption pressure across a business, map competitive exposure, and produce a 90-day defensive action plan.
🎯 Best For
- Data analysts
- Business intelligence teams
- Claude users
- Knowledge workers
- Remote teams
💡 Use Cases
- Finding patterns in customer data
- Creating automated dashboards
- Using moatmri in daily workflow
- Automating repetitive productivity tasks
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply moatmri to Your Work
Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.
- 4
Review and Refine
Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.
❓ Frequently Asked Questions
Can this connect to my database directly?
Most data skills accept CSV or JSON input. Database connectors are listed in the Works With section.
How do I install moatmri?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/moatmri/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Not validating data quality
AI analysis is only as good as your input data. Profile and clean data before analysis.
Not reading the full skill
Skills contain important context and edge cases beyond the quick start.