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Found 424 Skills
Pack entire codebases into AI-friendly files for LLM analysis. Use when consolidating code for AI review, generating codebase summaries, or preparing context for ChatGPT, Claude, or other AI tools.
Build with OpenAI's stateless APIs - Chat Completions (GPT-5, GPT-4o), Embeddings, Images (DALL-E 3), Audio (Whisper + TTS), and Moderation. Includes Node.js SDK and fetch-based approaches for Cloudflare Workers. Use when: implementing chat completions with GPT-5/GPT-4o, streaming responses with SSE, using function calling/tools, creating structured outputs with JSON schemas, generating embeddings for RAG (text-embedding-3-small/large), generating images with DALL-E 3, editing images with GPT-Image-1, transcribing audio with Whisper, synthesizing speech with TTS (11 voices), moderating content (11 safety categories), or troubleshooting rate limits (429), invalid API keys (401), function calling failures, streaming parse errors, embeddings dimension mismatches, or token limit exceeded.
Integrates SAP Cloud SDK for AI into JavaScript/TypeScript and Java applications. Use when building applications with SAP AI Core, Generative AI Hub, or Orchestration Service. Covers chat completion, embedding, streaming, function calling, content filtering, data masking, document grounding, prompt registry, and LangChain/Spring AI integration. Supports OpenAI GPT-4o, Claude, Gemini, Amazon Nova, and other foundation models via SAP BTP.
Produce an LLM Build Pack (prompt+tool contract, data/eval plan, architecture+safety, launch checklist). Use for building with LLMs, GPT/Claude apps, prompt engineering, RAG, and tool-using agents.
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)
Extract and structure personal context from AI chat transcripts into themed markdown files. Use when (1) Processing Claude, Claude Code, or other AI conversation exports, (2) Building personalized AI assistants from chat history, (3) Creating context files for Claude Projects, GPTs, or Gems, (4) Consolidating scattered knowledge from multiple conversations. Optimized for Claude Haiku.
Integrating local LLMs into Godot games using NobodyWho and other Godot-native solutionsUse when "godot llm, nobodywho, godot ai npc, gdscript llm, godot local llm, godot chatgpt, godot 4 ai, godot, llm, nobodywho, gdscript, game-ai, npc, local-llm" mentioned.
Write newsletter articles for The Hybrid Builder (chatwithgpt.substack.com) with intelligent cross-referencing of the full article archive. Includes sitemap-based article cache with theme indexing, reference suggestions, session transcript export, and cover image generation. Use when asked to write a blog post, article, or newsletter about a collaboration or technical topic.
Guide Claude through SCSA, MetaTiME, CellVote, CellMatch, GPTAnno, and weighted KNN transfer workflows for annotating single-cell modalities.
Chat with web AI agents (ChatGPT, Gemini, Claude, Grok, NotebookLM) via browser automation. Use when stuck, need cross-validation, or want a second-model review.
Shell out to Cursor Agent CLI for headless IDE-aware code tasks. Supports multi-model routing (auto mode routes to Claude, Gemini, GPT). Requires Cursor Pro/Business subscription.
Comprehensive prompt and context engineering for any AI system. Four modes: (1) Craft new prompts from scratch, (2) Analyze existing prompts with diagnostic scoring and optional improvement, (3) Convert prompts between model families (Claude/GPT/Gemini/Llama), (4) Evaluate prompts with test suites and rubrics. Adapts all recommendations to model class (instruction-following vs reasoning). Validates findings against current documentation. Use for system prompts, agent prompts, RAG pipelines, tool definitions, or any LLM context design. NOT for running prompts, generating content, or building agents.