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Found 9,218 Skills
Selects, deploys, and customizes AI models on Amazon SageMaker. Fine-tuning (SFT, DPO, RLVR, RLAIF), model selection, dataset preparation, evaluation, deployment to SageMaker endpoints or Bedrock, and endpoint diagnostics. Covers the full lifecycle from planning through production. Use when fine-tuning models on SageMaker, selecting base models from SageMaker Hub, finding a model to deploy without fine-tuning, transforming datasets for training, checking data readiness, evaluating model quality, deploying to endpoints, setting up IAM roles and S3 buckets for training jobs, or managing a SageMaker Managed MLflow app. Also use to check endpoint health, diagnose failures, debug latency or errors, or view container logs and CloudWatch metrics. Covers Serverless Model Customization, Nova and OSS deployment paths, and PySDK v3 usage. NOT for Ground Truth labeling, Feature Store, or general-purpose AWS infrastructure.
Guide for creating, structuring, and improving Claude skills (SKILL.md). Use when building a new skill, reviewing an existing skill, writing SKILL.md frontmatter, defining trigger conditions, troubleshooting skill problems (not triggering, over-triggering, instructions not followed), or planning skill distribution. When working on any skill in this repository: also load the cc-best-practices skill, and always update both CLAUDE.md and README.md skill tables after any skill change. Do NOT use for general Claude Code configuration or hook setup.
Handle files and binary data in n8n correctly. Use when working with files, images, PDFs, attachments, uploads or downloads, base64, vision/multimodal input, or when an AI agent needs a file as tool input or output — and whenever the user mentions $binary, binaryPropertyName, "read the PDF", "attach the file", "send the image", Merge losing binary, or a CDN for chat images. Covers the $binary vs $json split, reading/writing binary, keeping binary alive across transforms with Merge, the agent-tool binary boundary, and the CDN/URL requirement for chat surfaces.
Use when symfony executing plans
Quickly test and compare LLM models via OpenRouter. Find the fastest/cheapest model, compare response quality. Trigger words: openrouter, test model, compare models, find fastest model, find cheapest model
Execute complete FPF cycle from hypothesis generation to decision
Create and configure git hooks with intelligent project analysis, suggestions, and automated testing
Create and setup git worktrees for parallel development with automatic dependency installation
Load all open issues from GitHub and save them as markdown files
Create pull requests using GitHub CLI with proper templates and formatting
Curates insights from reflections and critiques into CLAUDE.md using Agentic Context Engineering
Reset the FPF reasoning cycle to start fresh