We planted 19 agent surfaces on a machine and ran geiger against them. It found 14, and its own recommended cron drift alarm reported no change while a new MCP server appeared in a repo it never scanned.
The index lists 53 skills, the repo holds 37, the plugin installs 25. We cloned the pack and measured the install: the context-bloat fear is half a percent.
We cloned book-to-skill and ran its own bench: 57.6x on our book - and identical on all five chapters. The denominator is a fixed 5,000-token design cap.
WASTE runs the complete 2.78T Kimi K3 on a 64 GB MacBook. It works – at 0.6 tokens a second, with a memory setting that makes it slower the more RAM you give it. The worth-it verdict.
I built the purple-gradient page every AI agent emits, then let Hallmark rebuild the same content and audited both. Ten critical slop-tells before, zero after. Here's the before and after — and the seam the demo hides.
OpenAI's GPT-5.6 Sol is the best knowledge-work model I've sat next to - fast, resourceful, steerable. It's just not the coding king the launch claims, and OpenAI's own numbers say so.
Fable 5 is back. There's no magic prompt - the whole skill is two moves: pick the right job, and make the model prove its work. Here are the ones I actually use.
The tool everyone adopted doesn't make your team smarter - it makes them louder. A hands-on verdict on signal-to-noise, slop cannons, and the one metric that actually sorts operators.
Three agent-stack bills landed at once this week. One - an actively-exploited LiteLLM RCE - has a June 22 clock on it. Here's the cut that matters, and what's safe to skip.
AI, measured
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