Results for “prompt”

Monitors OpenClaw model API usage and prompts for user confirmation before switching models when quota is low.

LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.

LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debug...

Popconfirm component for confirmation dialogs in popover style. Invoke when user needs to implement confirmation prompts, delete confirmations, or action verifications in Naive UI.

LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.

LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debug...

xAI Grok image and video generation guide covering authentication, endpoints, prompt structure, image editing, reference-image video, and async polling.

Create new skills, modify existing ones, and measure their performance through iterative evaluation and benchmarking.

Provides a Node.js CLI tool template with Commander.js, interactive prompts, and best practices for building command-line applications.

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debuggin

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

Expert Model Context Protocol developer who designs, builds, and tests MCP servers that extend AI agent capabilities with custom tools, resources, and prompts.

Generating AI image-generation code using the Gemini API. Handles text-to-image generation, image editing, and prompt optimization. Use when image generation code is needed.

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

Transform diverse inputs (YouTube videos/audio, existing Suno songs, raw lyrics, audio files, or conversational ideas) into highly optimized Suno V5 custom song generation prompts with intelligent character optimization (5000 lyrics, 1000 style limits), proven metatag reliability, V5-enhanced emotion tags, and template-based best practices. Use when user wants to create music with Suno, provides content for song generation, or needs help crafting effective V5 prompts.

Transforms lessons learned into domain-organized memory instructions that persist across VS Code contexts, with global and workspace scopes.

Create, list, and view GitHub issues interactively using the gh CLI, with guided prompts for titles, bodies, labels, and filters.

Backs up important files before modification, prompts the user to review changes, and deletes the backup only after explicit confirmation.

Generates a structured post-task reflection capturing surprises, patterns, prompt improvements, and gotchas, writing it to a markdown file without modifying project rules.

Generates video clips from text prompts using Google Veo models, with options for duration, aspect ratio, and model selection.

Create, list, and view GitHub issues interactively using the gh CLI, with guided prompts for titles, bodies, labels, and filters.

Research a topic from the last 30 days on Reddit + X + Web, become an expert, and write copy-paste-ready prompts for the user's target tool.

Research a topic from the last 30 days on Reddit + X + Web, become an expert, and write copy-paste-ready prompts for the user's target tool.

Build MCP servers with Node/TypeScript SDK — tools, resources, prompts, Zod validation, stdio vs Streamable HTTP. Use Context7 or official MCP docs for latest API.

Designing and evaluating AI/ML systems: prompt engineering, RAG design, LLM application patterns, AI safety, evaluation frameworks, MLOps, cost optimization. Use for AI pipelines or eval harnesses.

Research a topic from the last 30 days on Reddit + X + Web, become an expert, and write copy-paste-ready prompts for the user's target tool.

Use after the user has authorized GPT Pro help; manage a prompt-plus-sources workspace, route through ChatGPT Projects when available, and audit returned reasoning.

Audit agent skills, plugins, prompts, manifests, scripts, dependencies, and bundled assets for provenance, prompt-injection, permission, execution, exfiltration, persistence, and update risk. Use when evaluating a third-party skill before installing, enabling, updating, publishing, or distributing it; reviewing an untrusted SKILL.md, agent configuration, MCP integration, archive, or repository; comparing a package with a known-good version; or investigating unexpected tool, network, credential, or filesystem behavior.

Draws a Tarot spread to inject randomness into decision-making when prompts are vague or multiple approaches are equally valid.

Translates creative intent into technical cinematographic directives for Veo3, Kling, and Luma video models via muapi.ai.

Transforms rough sketches or text descriptions into photorealistic 3D renders using Vizcom's AI rendering modes and prompt weighting.