Glab

Developer skill for running Hummingbot and Gateway from source, building wheel and Docker images, and testing against Hummingbot API running from source. Use this skill when a developer wants to build, run, or test Hummingbot components locally.

Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.

Use this skill when the user wants to debug, diagnose, or systematically iterate on an experiment that already exists, or when they need a structured experiment log for tracking runs, hypotheses, failures, results, and next steps during active research. Apply it to underperforming methods, training that will not converge, regressions after a change, inconsistent results across datasets, aimless experimentation without progress, and questions like 'why doesn't this work?', 'no progress after many attempts', or 'how should I investigate this failure?'. Also use it for setting up practical experiment logging/record-keeping that supports debugging and iteration. Do not use it for designing a brand-new experiment pipeline or full experiment program (use experiment-pipeline), generating research ideas, fixing isolated coding/syntax errors, or writing retrospective summaries into research memory/notes/knowledge bases.

Build and deploy Streamlit apps natively in Snowflake. Covers snowflake.yml scaffolding, Snowpark sessions, multi-page structure, Marketplace publishing as Native Apps, and caller's rights connections (v1.53.0+). Use when building data apps on Snowflake, deploying SiS, fixing package channel errors, authentication issues, cache key bugs, or path resolution errors.

Deploy production recommendation systems with feature stores, caching, A/B testing. Use for personalization APIs, low latency serving, or encountering cache invalidation, experiment tracking, quality monitoring issues.

Data analysis, visualization, and storytelling skill for financial and RevOps contexts. Use when: analyzing revenue data, building forecasts, cohort analysis, churn modeling, pipeline analytics, creating data-driven reports, building dashboards, cleaning messy data, sanity-checking analytical claims, exporting to Excel with formulas, or extracting data from PDFs. Features decision logging, bias-aware interpretation, and progressive disclosure (slide deck -> detailed report -> full notebook with all decisions documented).