Solo MCN Self-Media Operations Knowledge Base

Problem

Solo creator workflows often break down when operations become fragmented: topic selection, titles, drafting, cover design, platform rules, analytics, and monetization are handled as one-off tasks. Solo MCN Domain organizes the one-person MCN process into a queryable domain pack with task lists, dependency edges, and component constraints. It is not an execution framework; it provides the structure that an execution layer can consume.

How It Works

The skill is built around Universal Task OS (UTOS) as the execution backend. On activation, it checks for universal-task-os. If unavailable, it drops into read-only reference mode and only allows browsing task catalogs, requirement lists, and exemplar indexes. In normal use, it reads references/mcn-catalog.md for domain classification and dependency topology, then reads references/mcn-requirements.md for required/optional components, assembly order, and platform constraints. It covers six modules:
- M1 Topic Planning: hot-topic tracking, topic generation, competitor analysis, topic evaluation
- M2 Content Creation: title optimization, body writing, SEO, video scripts, interaction prompts
- M3 Visual Design: cover proposals, color schemes, layout, image-generation prompts
- M4 Platform Operations: platform adaptation, community operations, fan interaction, cold start, cross-platform routing
- M5 Data-Driven Iteration: data collection, hit analysis, underperformance diagnosis, strategy iteration
- M6 Monetization: pricing, business communication, contract review, scheduling

It exposes chains such as M1-01 → M1-02 → M1-05 → M2-01 → M2-02 → M4-01 as pipeline inputs for UTOS, while flagging platform differences in title length, body length, tag count, cover size, sensitive words, and superlative claims.

Boundaries

The skill does not replace drafting, design, publishing, or analytics tools, and it does not include an execution engine. Without UTOS, it is limited to reference lookup and cannot produce complete deliverables or derive operation pipelines. Most exemplars entries are marked to be filled, so sample-based reuse is limited until users add sanitized examples. Platform rules change over time; outputs should keep verification notes, and humans must confirm before publishing.