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Found 1,834 Skills
Guides the user through distributing Tauri applications via CrabNebula Cloud, including pipeline setup, cloud configuration, auto-updates integration, and CI/CD workflows for seamless app distribution.
This skill should be used when creating or configuring CI/CD pipeline files for automated testing, building, and deployment. Use this for generating GitHub Actions workflows, GitLab CI configs, CircleCI configs, or other CI/CD platform configurations. Ideal for setting up automated pipelines for Node.js/Next.js applications, including linting, testing, building, and deploying to platforms like Vercel, Netlify, or AWS.
Diagnose ClickHouse INSERT performance, batch sizing, part creation patterns, and ingestion bottlenecks. Use for slow inserts and data pipeline issues.
MongoDB query optimization and indexing strategies. Use when writing queries, creating indexes, building aggregation pipelines, or debugging slow operations. Triggers on "slow query", "create index", "optimize query", "aggregation pipeline", "explain output", "COLLSCAN", "ESR rule", "compound index", "partial index", "TTL index", "text search", "geospatial", "$indexStats", "profiler".
Creates, configures, and updates Databricks Lakeflow Spark Declarative Pipelines (SDP/LDP) using serverless compute. Handles streaming tables, materialized views, CDC, SCD Type 2, and Auto Loader ingestion patterns. Use when building data pipelines, working with Delta Live Tables, ingesting streaming data, implementing change data capture, or when the user mentions SDP, LDP, DLT, Lakeflow pipelines, streaming tables, or bronze/silver/gold medallion architectures.
Orchestration pattern for sequential, dependent tasks. When work must flow through stages where each stage depends on the previous (design → implement → test → review), structure as a pipeline with explicit handoffs. Each stage completes before the next begins.
Outbound sales methodology based on Aaron Ross' "Predictable Revenue". Use when you need to: (1) build a scalable outbound sales process, (2) implement Cold Calling 2.0, (3) structure sales team roles (SDR/AE/CSM), (4) design lead generation and qualification frameworks, (5) scale B2B SaaS sales predictably, (6) create prospecting email sequences, (7) build sales development pipeline, (8) separate prospecting from closing.
Analyze and optimize pytest suites to improve speed, identify flaky tests, and increase coverage. Use to maintain high-quality, fast-running test pipelines.
Implements the Chain of Responsibility pattern in Python. Use when the user mentions chain of responsibility, CoR, or when you need to chain handlers that each process and pass to the next—validation pipelines, processing steps, transformation chains, or any sequential pipeline.
Reporting pipelines for CSV/JSON/Markdown exports with timestamped outputs, summaries, and post-processing.
Write ML experiment code with iterative improvement. Generate training/evaluation pipelines, debug errors, and optimize results through code reflection. Use when implementing experiments for a research paper.
Set up GitHub Actions workflows for CI/CD with automated testing, linting, and deployment for Python/UV projects. Use when creating CI pipelines, automating tests, or setting up deployment workflows.