Skill UI

Generates high-quality, short video clips (3-15s) using the Seedance 2.0 model. It accepts structured English prompts, an optional starting frame image, and style/identity reference images to ensure character and visual continuity. Supports multiple cloud backends (OpenRouter, Volcengine, BytePlus), making it ideal for storyboarding, cinematic concept visualization, or short film pre-production.

This skill enables the creation and registration of reusable cloned voices from local audio samples for subsequent Text-to-Speech (TTS) applications. It implements a strict 'Consent-first' workflow, requiring explicit user consent, detailed metadata (speaker, permitted use), and adherence to copyright laws before any voice cloning can occur. It ensures the resulting voice ID is safe, traceable, and legally compliant for professional content creation.

A comprehensive studio for professional voice conversion. This tool allows users to transform local audio recordings into specific, authorized target voices. It manages complex workflows, requiring rigorous checks on source rights, target voice licensing, and detailed parameters like emotion, accent, pace, and language locale, ensuring compliance and high-quality output.

Use Voiceover Studio to convert written scripts into high-quality, professional audio narration. This tool supports diverse applications including product demos, IVR prompts, podcast episodes, and short-video voiceovers. It manages complex requirements such as specific accents, emotions, speaking pace, and precise language/locale preservation, ensuring the resulting audio is ready for immediate use.

This skill provides a comprehensive guide for building scalable Retrieval-Augmented Generation (RAG) pipelines and persistent agent memory using Pinecone as the vector database. It covers index setup, embedding large corpuses, implementing dense and hybrid semantic search, and advanced metadata filtering for real-world production systems. Use this for building searchable knowledge bases and context-aware AI agents.

This skill guides the process of routing a complex goal through an AI's scored-memory loop using the `acc_act(runtime="solve")` function. It provides a structured workflow for deliberation, handling intermediate `brain_frame` results, and submitting continuous proposals. It emphasizes systematic reasoning and requires careful resolution of all generated frames to ensure a robust and verifiable solution.

A specialized quality gate skill designed to review complex, multi-source outputs generated by the CrossFrame framework. It rigorously checks reasoning fidelity, evidence boundaries, source anchors, and structural continuity. Use this when advanced verification of logical rigor and source integrity is required, ensuring outputs meet strict internal protocols and avoid common structural failures.

Conducts a comprehensive, structured ethical review for any AI or ML model, feature, or product. It assesses risks related to fairness, bias, transparency, privacy, and societal impact, providing a risk tier score, necessary mitigations, and governance documentation suitable for pre-deployment compliance.

This skill implements the LLM Council concept, enabling multiple open-weight language models to collaborate on complex queries. The process follows a three-stage deliberation: 1) Parallel independent responses from selected models; 2) Peer-to-peer ranking of the responses; and 3) Final synthesis by a designated Chairman LLM. Powered by Fireworks AI, it ensures deep, multi-faceted analysis and consensus building for high-stakes decision support.

This skill assists users in defining, adapting, and designing bounded, structured feedback loops for AI agents. Whether you need to find a suitable existing workflow, fine-tune a published loop, or design a new process from scratch, this tool guides you through a safe, iterative methodology. It emphasizes setting clear stopping rules, guardrails, and verifiable, measurable steps to ensure the automation remains controllable and focused.

Deploy and operate Falco with the modern eBPF driver in Kubernetes and Docker. Covers driver selection, Helm installation, output channels, and the built-in ruleset that detects container escape, namespace abuse, privileged mounts, and anomalous syscalls. Ideal for enabling runtime security, routing alerts to SIEM or Falcosidekick, and upgrading existing deployments.

Implements a comprehensive defense-in-depth framework for autonomous AI agents that interact with external tools. It mitigates risks like prompt injection or tool misuse by enforcing strict tool allowlisting, binding tools to least-privilege identities, requiring human-in-the-loop approval for high-impact actions, and utilizing policy enforcement (like NeMo Guardrails) to bound the blast radius and ensure compliance.