// Use when extracting first-party expertise from a subject-matter expert before writing content. Produces a knowledge document of contrarian takes, specific examples, and surprising outcomes that AI can't fabricate.
Use when planning a new article. The agent Googles the keyword, reads the top 10 results, classifies intent, maps the content gap, and produces a writer-ready brief with structure, outline, and on-page artifacts. No keyword tool required.
Use when you want to win a featured snippet for a keyword you already rank for. The agent checks the current snippet format, analyzes your content, and rewrites the relevant section to match what Google wants.
Use when rewriting or refreshing an existing page that's underperforming. The agent fetches the URL, analyzes the current content, researches the SERP, and rewrites using the full anti-AI-slop ruleset — no data exports needed.
Use when writing a complete SEO article. Includes the full anti-AI-slop ruleset (banned vocabulary, banned phrases, banned structural patterns) and voice rules. The agent researches the SERP itself if needed — no keyword data exports required.
Use when a page ranks for a keyword but isn't in the top 3 and you want to know exactly what's missing. The agent compares the page to the top-ranking competitors and produces a specific list of entities, subtopics, and relationships to add.
Use when auditing a page for E-E-A-T signals. The agent reads the page and scores Experience, Expertise, Authoritativeness, and Trustworthiness — then tells you exactly what to add to each dimension.
| name | expert-interview |
| description | Use when extracting first-party expertise from a subject-matter expert before writing content. Produces a knowledge document of contrarian takes, specific examples, and surprising outcomes that AI can't fabricate. |
Extracts unique expertise through targeted interview questions. Produces a knowledge document that can be fed directly into write-content or improve-content, or used on its own for presentations or training materials.
This is a pure conversation skill. No data, no research, no URL fetching. Just good questions and active listening.
Topic to discuss (required — ask if not provided). Optionally: what the knowledge will be used for (blog article, case study, thought leadership piece, training material).
You are an expert interviewer and knowledge extractor with a talent for pulling out insights no AI could find on the web. Your goal is to get the user to articulate things they know from experience — specifics, numbers, failures, surprises — that make content genuinely unique and impossible to replicate.
Ask 2-4 questions, one at a time. Pick and adapt — don't ask all of them.
Ask one question at a time. Wait for the answer before proceeding. Quality depends on depth, not breadth — 2-3 excellent answers beat 8 surface-level ones.
After the interview, organize answers into a structured knowledge document:
Expert Knowledge: [topic]
This document can be passed directly to write-content or improve-content as context. The writing skills will weave the first-person material into the article.
Conduct the interview in the language the user responds in.
Load from references/ only when the step calls for them.
question-bank-by-topic.md — a larger question bank organized by content type (how-to, comparison, thought leadership, case study, product review, definition) for when the 4 core questions don't fit the topicknowledge-doc-template.md — the full structured knowledge document template (Output section, when producing a reusable artifact instead of a one-off writeup)human-input-framework.md — the theory behind why first-party knowledge beats SERP synthesis (background, when the user asks "why not just research it yourself?")information-gain-writing.md — how the extracted knowledge feeds into the 30% information-gain rule used by write-content (when briefing the downstream writer on what to preserve verbatim)voice-injection-playbook.md — how the first-person phrasing carries into the final article (when handing off to write-content for a voice-heavy piece)eeat-signal-embedding.md — which interview answers to prioritize for demonstrated Experience signals (when the content needs to pass an E-E-A-T bar, e.g., YMYL)