Claude Skills become self-improving systems when you add evals and memory. Peter Yang's tutorial walks through a concrete five-step build: inject personal context and examples, tune the trigger description for reliable activation, create an eval loop where Claude identifies and fixes its own output errors, attach memory so the skill updates itself from past corrections, and build a skill editor to manage all skills from one interface.
The eval loop at step three is the technical core worth your attention. Rather than manually reviewing every output, the system prompts Claude to score its own work against your criteria and rewrite failures automatically. Step four compounds this by storing corrections as persistent memory, so the skill gets measurably better across sessions without human intervention. The build vehicle is an /edit-post skill for long-form writing, which keeps the example grounded and replicable.
The final section, at 17:44, addresses where human taste still overrides automation. That tension, between automatable craft and irreducible judgment, is where the real argument lives. Read the full written tutorial at creatoreconomy.so for the exact prompts and architecture.
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