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Autonomous deep-work agent loop for driving projects forward. Each invocation: reads project state, applies critical expert thinking, executes one focused unit of work, persists to notebook + PROJECT_STATE.md. Sets up /loop cron on first run (default 10m). Three-tier confidence gate (GREEN/YELLOW/RED) blocks action when human input is needed. Invoke ONLY via /liquid-cat-physics or 'lcp' — do NOT t

The process I experienced firsthand through the https://anthropic.skilljar.com/claude-code-in-action course using real-world daily projects

An AI agent skill for interacting with your Obsidian vault via the CLI — works with Claude Code and Cursor

Context handoff for fresh sessions. Saves unsaved session knowledge to notebook, then produces a short orientation block to paste into a new chat. Use when user says '/memento', 'hand off context', 'prepare for fresh chat', 'save and brief', or before clearing context. NOT for: recovering context (use /notebook recover) or saving a single note.

Clerk for reserve reduction, trespass, survey errors, and railway takings; use when processing the Land_Reduction_Trespass queue.

Implemente estratégias de avaliação abrangentes para aplicações LLM usando métricas automatizadas, feedback humano e benchmarking. Utilize ao testar o desempenho de LLMs, medir a qualidade de aplicações de IA ou estabelecer estruturas de avaliação.

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing.

Comprehensive healthcare AI toolkit for developing, testing, and deploying machine learning models with clinical data. This skill should be used when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, drug recommendation), medical coding systems (ICD, NDC, ATC), physiological signals (EEG, ECG), healthcare datasets (MIMIC-III/IV, eICU, OMOP), or implem

SOLID object-oriented design principles for maintainable code

Padrões modernos de desenvolvimento de API para serviços web de alto desempenho e escaláveis, abrangendo async/await, REST/GraphQL, middleware, tratamento de erros, limitação de taxa, OpenAPI, testes e otimizações de produção. Estes padrões agnósticos de framework são aplicáveis a Python, Node.js, Go e outras linguagens.

Coordinates multi-step CI/CD pipelines by chaining autonomous-ci, code-review, smart-commit, and jules-integration plugins. Use when executing validation-to-PR workflows or recovering from CI failures.

Builds automated sports analytics pipelines -- daily data pulls, scheduled prediction generation, model versioning, prediction tracking, and drift alerting. Use when user asks how to automate their model, how to run predictions every morning, how to set up a cron job for sports data, how to track model performance over time, or how to version their model. Do not use for one-time data pulls -- use