Skill UI

Provides comprehensive configuration management for local LLM inference using RuVLLM. Users can select models, perform task-specific fine-tuning with MicroLoRA adapters, or implement continuous, real-time adaptation using SONA. This tool guides the entire advanced LLM workflow, covering status checks, configuration generation, and advanced adaptation loops.

This skill runs a single, simulated tick of a defined business pod (Sales). It is designed for dry-run testing, allowing users to validate inputs, resolve agents, and reserve budgeted resources without invoking real LLM workers. It handles template loading, schema validation, budget management, and emits structured status reports for subsequent workflow consumption.

This tool automates the process of optimizing investment portfolio allocations using a mean-variance engine. It integrates neural prediction models and risk constraints to determine optimal asset weights. Users can set specific risk targets, assess comprehensive risk metrics (variance, correlation), and generate actionable, step-by-step rebalancing plans for professional portfolio management.

This skill guides users through creating or updating a comprehensive brand profile. It supports new client onboarding, detailed business profiling (including industry, USP, and business model), and brand voice calibration. Whether performing a quick setup or a full deep dive, it ensures all subsequent marketing content and strategies are perfectly aligned with the brand's identity.

This comprehensive skill guides the end-to-end planning of influencer and creator partnerships. Use it for discovering authentic creators, building detailed campaign briefs, ensuring FTC compliance, measuring performance (ROAS, EMV), and managing user-generated content (UGC) strategies across multiple platforms. It covers everything from vetting creators to handling international compliance.

A comprehensive tool for managing high-performance GPU resources via Itô Compute. It allows users to query live GPU inventory, submit authenticated fixed-rate Requests for Quote (RFQ), inspect procurement status, and run explicit node qualification tests. This system is designed for finding capacity (e.g., H100/H200) and validating node readiness for compute workloads.

Generate professional, brand-aligned responses for online reviews (positive, neutral, and negative). This tool ensures responses maintain consistent brand voice, adhere to compliance rules, and are optimized for the specific platform (e.g., Google, Yelp). It guides users through best practices for reputation management, offering actionable follow-up notes and escalation recommendations.

The Unified Memory system provides a durable, inspectable context layer for sharing state and handoffs between multiple autonomous agents (harnesses) like Claude, Codex, and Hermes. It allows agents to save work state, transfer context, resume tasks, and search shared project knowledge across different scopes (project, team, user).

Provides a comprehensive guide to the Academy of Management Journal (AMJ) editorial and peer-review process. It details the stages from desk review to final decision letter interpretation. Users learn how to distinguish between fatal and fixable concerns, prioritize the action editor's feedback, and strategically plan deep, multi-round revisions, turning feedback into actionable research improvements.

This guide provides detailed standards for formatting empirical results (tables and figures) for the Academy of Management Journal (AMJ). It covers best practices for reporting correlation matrices, regression/SEM/HLM results, theoretical model diagrams, and interaction plots, ensuring adherence to strict academic publishing house styles (AOM house style). It helps users create self-contained, publication-ready exhibits.

This comprehensive workflow acts as a systematic router for authors writing empirical management papers for the Academy of Management Journal (AMJ). It guides users through the entire research lifecycle—from initial topic selection and theory development, through rigorous methodology and data analysis, to refining writing style, and finally managing the submission and rebuttal process. It ensures the manuscript meets the high standards of theoretical and empirical contribution required by top-tier academic journals.

This comprehensive workflow guides authors through the complex, multi-stage process of developing a purely theoretical contribution for an Academy of Management Review (AMR) submission. It acts as a router, directing the user to specific specialized skills at each point of the scholarly writing process, from topic selection to contribution framing and final polish. It emphasizes that the deliverable is pure theory, not empirical data.