Claude Code instructions for houshuang/limbic, covering limbic — ai agent guide, rules of thumb, always whiten domain-focused corpora, always genericize number-heavy text and clustering thresholds depend on whitening.
Instructions for tecton-ai/tecton-mcp, covering claude configuration for tecton feature development, tecton feature development rules, general feature creation guidelines, feature view selection rules and sql handling and data source references.
Instructions for tommyvo/useful-prompts, covering copilot instructions for useful prompts, project overview, repository structure, architecture: four platforms, one prompt library and 4. cursor skills (cursor/skills/ /skill.md).
Instructions for coeusyk/personal-notes-assistant, covering personal-notes-assistant, architecture, adding a tool, milvus notes (non-obvious, bit people twice already) and running / testing locally.
Instructions for AiAgentKarl/aviation-mcp-server, covering aviation mcp server — projektanweisungen, projektübersicht, tech stack, konventionen and architektur.
A set of instructions for Claude Code describing when and how to use DeepSeek Eyes, a tool for understanding images. It covers pasted or uploaded images that the model cannot see and processing several images at once.
Claude Code instructions for dmmdea/offload-harness, covering claude.md — agent orientation map for offload-harness, components & ports, model tiers (served by llama-swap on :11436), golden commands (all verified on this machine) and install / verify the stack (windows).
Instructions for AdamManuel-dev/prompt-template-engine, a project described as: Automated Prompt Optimization System for Cursor, Claude Code, VS Code, and anything else.
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Copilot instructions for kimtth/azure-ml-finetuning-eval-skills, covering github copilot custom instructions, available skills, training flow (azure-ml-llm-trainer), dataset generation (azure-ml-dataset-creator) and evaluation (azure-ml-model-evaluation).
Repository instructions for an image-understanding setup that lets an AI assistant analyze pictures using a vision model. They require the assistant to ask about the provider, API key, and model before configuring it.
Instructions for berrydev-ai/super-mcp-server, covering super mcp server development guide, project overview, core architecture, code style guidelines and planning phase.