Detect KB gaps and auto-draft articles with GPT-4.1, Slack and Gmail

Who is this for?

Support teams, knowledge managers, and ops builders who are drowning in outdated KB articles and repeat tickets. If your team keeps answering the same questions because your knowledge base has gaps nobody has time to find — this template finds them automatically and writes the first draft for you.

What does it do?

This is a complete multi-agent AI pipeline — 31 nodes across 7 pipeline stages that automate the entire KB maintenance lifecycle:

- Gap analysis — An AI agent cross-references your recent support tickets against your existing KB articles and identifies what's missing, what's weak, and what's stale. - Automated article drafting — For every gap found, a second AI agent writes a complete KB article draft using your actual ticket data as context. - Quality review — A third AI agent scores each draft on accuracy, completeness, and clarity — so you know what's ready to publish and what needs work. - Health scoring — A fourth AI agent generates a comprehensive health report with a 0-100 score, letter grade, executive summary, and prioritised action items. - Dual notifications — Results are delivered via both Slack (rich blocks) and Gmail (polished HTML email) with color-coded health scores, gap tables, and action items. - Staleness detection — Flags existing articles that haven't been updated in configurable timeframes. - Scheduled automation — Runs daily on a cron schedule (or manually on demand).

How it works

The Configuration node defines your helpdesk API endpoints, notification settings, and thresholds. The pipeline fetches recent tickets and current KB articles via HTTP, normalises the data, then sends it to the Gap Analysis Agent (GPT-4.1).

If gaps are found, each gap is split into an individual item and routed through the Article Drafter Agent → Quality Reviewer Agent pipeline. In parallel, a Staleness Check flags outdated articles.