Checks whether an author's LinkedIn Article(s) are cited by LLM engines (ChatGPT, Perplexity, Google AI Overview, Claude.ai web). Runs a list of ICP queries, records citations, and computes share-of-voice. Run 4+ weeks after publishing an Article.
Builds a Voice Vocabulary for an author — a dictionary of their characteristic phrases, turns of speech, fillers, metaphors, and contrarian formulas. Used as a humanization layer on top of the DIP. Collected ONLY from raw sources (transcripts, voice input, personally written Telegram posts), NEVER from the author's LinkedIn posts.
Checks a LinkedIn post for factual accuracy. Finds statements compiled from multiple sources and verifies logical integrity. Use after creating a post or whenever facts need to be verified.
Checks content for generic / abstract phrasing, AI language, and repetition from the author's previous posts. Supports two-pass mode — the first pass catches original issues, the second (--second-pass) verifies that the humanizer didn't introduce new generic phrases.
Transparently shows where each key idea in a LinkedIn post comes from. Builds a source map. Lets you exclude specific sources.
Writes a LinkedIn comment on SOMEONE ELSE's post on behalf of an author. Loads the author's DIP, analyzes the post, picks a formula, and checks source grounding. Use when you need to comment on another person's post.
Creates a LinkedIn Article (long-form Pulse, 1000-2000 words) optimized simultaneously for AI-search (GEO) and the LinkedIn algorithm. Use when long-form content is needed with the goal of LLM citations. 8-step pipeline with a mandatory GEO checklist.
Creates a Digital Identity Profile (DIP) for a new author from scratch. Collects raw sources (transcripts, voice, Telegram), extracts Tone of Voice, Stories Bank, Expertise Clusters. ONLY from raw sources, NEVER from posts.