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Found 408 Skills
Step-by-step analysis for complex problems — multi-step reasoning, hypothesis verification, adaptive planning with revision.
Systematic problem-solving techniques — inversion, collision-zone, scale-game, simplification cascades.
KERNEL-based prompt engineering — transforms vague requests into structured, high-performance prompts optimized for first-try success.
Use this skill whenever the user wants to interact with an n8n instance via its public REST API. Triggers include: listing, creating, updating, deleting, activating or deactivating workflows; viewing or managing executions; managing credentials, tags, variables, users, or projects; auditing instance activity; triggering workflow runs; checking execution status; or any automation task involving the n8n API. Also use for requests like "show my n8n workflows", "run workflow X", "list failed executions", "create a tag in n8n", "manage n8n variables", or "check n8n audit log". Always use this skill for any n8n API interaction — it defines the correct endpoints, authentication, and patterns.
Complete Python gotchas reference. PROACTIVELY activate for: (1) Mutable default arguments, (2) Mutating lists while iterating, (3) is vs == comparison, (4) Late binding in closures, (5) Variable scope (LEGB), (6) Floating point precision, (7) Exception handling pitfalls, (8) Dict mutation during iteration, (9) Circular imports, (10) Class vs instance attributes. Provides: Problem explanations, code examples, fixes for each gotcha. Ensures bug-free Python code.
Complete fal.ai image-to-video system. PROACTIVELY activate for: (1) Kling 2.5/2.6 Pro image animation, (2) MiniMax Hailuo with prompt optimizer, (3) LTX image-to-video, (4) Runway Gen-3 Turbo, (5) Luma Dream Machine with loop, (6) Stable Video Diffusion, (7) Motion description prompts, (8) Portrait/product animation workflows. Provides: Model endpoints, motion keywords, animation techniques, workflow examples. Ensures natural image animation with proper motion description.
Production-grade fault tolerance for distributed systems. Use when implementing circuit breakers, retry with exponential backoff, bulkhead isolation patterns, or building resilience into LLM API integrations.
Fetch GitHub issues, PRs, repo contents, and code using the gh CLI. Use when the user shares GitHub URLs (issues, PRs, repos, source files) or asks about GitHub content. The gh CLI provides complete content that web fetching often misses due to JavaScript rendering.
OrbStack-optimized Skaffold workflows for local Kubernetes development without port-forward. Use when configuring Skaffold with OrbStack, accessing services via LoadBalancer or Ingress, or when the user mentions OrbStack, k8s.orb.local, service access, or eliminating port-forward.
Work with state-of-the-art machine learning models for NLP, computer vision, audio, and multimodal tasks using HuggingFace Transformers. This skill should be used when fine-tuning pre-trained models, performing inference with pipelines, generating text, training sequence models, or working with BERT, GPT, T5, ViT, and other transformer architectures. Covers model loading, tokenization, training with Trainer API, text generation strategies, and task-specific patterns for classification, NER, QA, summarization, translation, and image tasks. (plugin:scientific-packages@claude-scientific-skills)
Git 2.49+ features including git-backfill, path-walk API, and performance improvements
Detect unused dependencies in Rust projects for cleaner Cargo.toml files and faster builds. Use when auditing dependencies, optimizing build times, cleaning up Cargo.toml, or detecting bloat. Trigger terms: unused dependencies, cargo-machete, dependency audit, dependency cleanup, bloat detection, cargo-udeps.