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Found 2 Skills
Create lean-spec style GitHub issues as specs for human-AI aligned implementation on the current repo. Use when asked to "create a spec", "write a spec issue", "spec this feature", "spec this", or when planning work that needs a specification before implementation. Follows the lean-spec SDD methodology — small focused specs (<2000 tokens), intent over implementation, context economy. Creates GitHub issues with Overview, Design, Plan, Test, Alignment, and Notes sections. Repo-specific area taxonomy, sister-skill names, custom body sections (e.g. Provider impact / Schema impact / Reach), and additional principles are overlaid by the consumer repo's CLAUDE.md and its `*-dev-process` / `*-pre-push` / `*-pr-lifecycle` sister skills — read those first when the repo isn't obvious.
Strategic guidance on AI scaling laws, capability trajectories, and building products at the frontier of AI capabilities. Use when users ask about AI scaling trends, capability forecasting, planning AI product development timelines, understanding pretraining vs reinforcement learning phases, interpreting AI benchmark improvements, deciding when to build AI products that don't quite work yet, or strategizing around rapidly advancing AI capabilities. Also triggers for questions about task horizon doubling, Jevons paradox in AI, or how to position products for future model improvements.