What problem does it solve? Writing LinkedIn posts that match a specific author voice, audience, and objective is time-consuming, and generic AI output often sounds robotic or makes unsupported claims. This Skill transforms project context, inherited verbal-language rules, and post-specific input into a complete, ready-to-publish LinkedIn post saved to a defined output file. ## Core Features & Use Cases - Adaptive Post Composition: Dynamically selects the objective, audience, hook, structure, tone, length, CTA, and hashtags from available input instead of forcing a fixed template. - Claim and Evidence Safety: Classifies every statement as confirmed, inferred, or missing, and refuses to invent metrics, names, or outcomes. - Brand Voice Inheritance: Reads verbal-system.md and related context files to apply established voice principles, terminology, and claim rules. - Use Case: A developer finishing a project showcase asks for a recruiter-oriented post; the Skill asks only the missing critical questions, then writes a complete caption with hashtags and asset notes to output/LinkedIn captions/linked-in-caption.md. ## Quick Start Use the linkedin-post-system skill to write a LinkedIn post announcing my project launch for a recruiter audience.
