Mit Ai Studio Hw3 — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Mit Ai Studio Hw3 (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
An MCP server built with Smithery CLI
This weather app has two functions: get alert and get forecast. Get alert gets any weather alert within the U.S. state, and get forecast gets the weather forecast for that location.
To make things more interesting, if you ask the it to speak in a pirate like tone, it can answer your requests with such a tone.
uv run dev uv run playgroundTry saying "Say hello to John" to test the example tool.
Your server code is in src/hello_server/server.py. Add or update your server capabilities there.
Ready to deploy? Push your code to GitHub and deploy to Smithery:
git add .
git commit -m "Hello world 👋"
git remote add origin https://github.com/YOUR_USERNAME/YOUR_REPO.git
git push -u origin main~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.