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Fal AI Media Generation

sickn33/agentic-awesome-skills

Generate images and videos using fal.ai AI models by resolving prompts, aspect ratios, durations, and budgets, then submitting the smallest bounded job through a verified fal.ai integration and reporting job status.

AI Image and Video Upscaling

sickn33/agentic-awesome-skills

Upscale and enhance images and videos with AI upscalers. Covers resolving target dimensions and scaling factors, verifying input schemas and upload authorization, and comparing returned artifacts against the source. Note that more pixels do not guarantee recovered real detail.

Fal Workflow Generator

sickn33/agentic-awesome-skills

Generate workflow JSON files for chaining AI models on fal.ai. Create reviewable graphs for multi-step media workflows, resolve inputs/outputs/dependencies, and validate model schemas. Use for planning authorized runs through available integrations.

AI Scientific Thinking Protocol

sickn33/agentic-awesome-skills

This skill implements a five-stage scientific thinking protocol for AI agents to prevent unverified guesses. It guides agents to formulate falsifiable hypotheses, seek evidence, and draw calibrated conclusions, especially for high-stakes or ambiguous questions. It includes modes for incidents, simple facts, estimates, and deep analysis, ensuring rigorous reasoning before answering.

Famulor MCP Workspace Operations

sickn33/agentic-awesome-skills

Operate Famulor voice AI assistants, calls, campaigns, messaging, knowledge, telephony and workspace settings through the hosted Streamable HTTP MCP server. Discover live tools, pick the smallest toolset, verify changes, and respect authorization boundaries.

Integrating Google Gemini API for AI Projects

gemini-api-integration

sickn33/agentic-awesome-skills

This comprehensive guide covers all aspects of integrating the Google Gemini API into your applications using Python or Node.js. It details basic text generation, advanced multimodal inputs (text, image, audio), streaming responses, function calling/tool use, multi-turn chat implementation, and production best practices like model selection and robust error handling.

Gemini Omni Flash Video Generation

gemini-omni-flash-api

sickn33/agentic-awesome-skills

Generative video editing, text-to-video, image-referenced video generation, and first-frame-to-video transition animations using the official google-genai SDK. Supports video editing, style transfer, inpainting/outpainting, and interpolation.

Gemini Media Generation Tool

generate-nanobanana

sickn33/agentic-awesome-skills

Generate and edit images and videos using Google's Gemini media models (Nano Banana 2/Pro, Gemini Omni Flash) with cost-approval gates, reference-image support, and detailed logging per call. Supports on-brand generation from reference sets and multi-image fusion for consistent character series.

AI Citability Scoring Optimization

sickn33/agentic-awesome-skills

This skill evaluates content for AI citability based on research from Princeton and Georgia Tech. It scores content on answer block quality, self-containment, and structural readability to optimize visibility in AI-generated responses. Ideal for SEO and GEO strategies to ensure AI models extract and cite your content effectively.

Geoffrey Hinton AI Persona Agent

geoffrey-hinton

sickn33/agentic-awesome-skills

This skill simulates Geoffrey Hinton, the Turing Award winner and father of deep learning. It provides expert insights on backpropagation, neural networks, deep belief networks, and capsule networks. Use this when discussing Hinton's contributions or advanced AI concepts.

Deep Multi-Source Research Synthesis

sickn33/agentic-awesome-skills

This advanced workflow is designed to generate comprehensive, fact-checked research reports on any complex topic. It systematically performs fan-out web searches across multiple defined angles, fetches multiple sources, and employs a rigorous adversarial verification system (3-vote) to validate claims. The final output is a highly cited, synthesized report, ideal for academic or critical business research.

Persistent Agent Goal Loop Orchestration

sickn33/agentic-awesome-skills

The /goal command converts standard agent prompts into persistent, self-correcting loops (plan → act → test → review → iterate). It is designed for long-running, complex engineering tasks like migrations, coverage lifts, or refactoring, ensuring progress is tracked against a verifiable stop condition and mandated documentation.

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