Cap Horizon — self-directed sports research and data visualization.
Original Edmonton Oilers analysis published November 1, 2026. It reconciles dated public cap estimates with official contract announcements and NHL/NHLPA rules across four seasons.
Current, projected and deadline cap space are kept distinct. Roster-floor and replacement-cost scenarios are labeled instead of treating an incomplete future roster as spendable room. The article includes transparent calculations, linked sources and an original raised-card visual.
AI-assisted research and writing with source, arithmetic and layout checks. This is self-published editorial work, not a client commission or an official NHL cap calculation. Figures and projections are dated in the article.
Keeping the research plan and cited results side by side is a useful way to make the agent’s work easier to inspect. I’d lean toward light mode for reading the table in daylight. How do you distinguish a verified source from one that still needs review?
Would you run a command without knowing what it could do?
A copied installation script. An automated workflow. A shell command suggested by AI.
Convenient? Yes. Worth checking before execution? Absolutely.
That’s why I built SafeShell, an open-source tool for inspecting commands, applying security policies, and running permitted commands with sandboxing on Linux.
The goal: help developers and engineering teams work faster with more control over what they execute.
Building automation or CI/CD workflows that need stronger security controls? I’m available for freelance projects in DevSecOps, secure automation, and cloud security. Let’s talk through Contra.
Useful idea, especially for commands suggested by AI. In my deploy script every step is logged, but nothing checks a command before it runs. Can SafeShell also run inside CI, for example as a step in GitHub Actions?