social-media

The social-media skill is an autonomous content generation agent designed for professional social media management on LinkedIn and Twitter/X. It follows a rigorous research-first workflow, ensuring that every post is backed by contextually relevant information retrieved by dedicated researcher subagents. This tool is ideal for content creators, social media managers, and technical writers looking to automate the creation of high-impact threads, professional updates, and engaging captions while maintaining a consistent brand voice.

• Automated research integration using the task tool to fetch topic-specific data before drafting.

• Intelligent hook generation and structure planning for both long-form LinkedIn posts and multi-tweet Twitter/X threads.

• Native image generation capabilities using generate_social_image to produce high-contrast, visually compelling assets tailored for social feeds.

• Platform-specific formatting that adheres to character limits, hashtag optimization, and line-break readability standards.

• Structured output management, automatically saving content to markdown files and images to categorized directories for version control.

• Users should initiate the skill with requests such as writing a LinkedIn post about a specific technology, creating a thread for a launch, or repurposing existing content for social distribution.

• The agent enforces a strict dependency: a research file must be saved in the research/ directory before post drafting begins.

• Every output must include a corresponding visual; the agent uses square or 4:5 aspect ratio images designed for optimal performance in crowded feeds.

• Constraints include platform-specific character limits (e.g., 280 characters for Twitter, ~1,300 for LinkedIn) and a requirement for minimal text within images to ensure readability.

• Effectiveness is measured by the quality of the hook, the relevance of hashtags, and the successful execution of the full research-to-generation pipeline.