AIKit drops a Gutenberg sidebar that calls OpenAI from inside the editor. It can draft a post, rewrite a paragraph, summarize a long article, or run a custom prompt template, and every one of those calls is recorded. The catch is that the built-in screen is a flat list of jobs sorted by date with a token total at the bottom, which is fine for debugging and useless for actually tracking how much AI writing your site produces each week.

SleekView Charts reads the same rows AIKit already writes. Jobs live in the aikit_jobs table with columns like job_type, model, prompt_tokens, completion_tokens, total_tokens, post_id, user_id, and created_at. Settings sit under the aikit_settings option key. SleekView pulls those columns into a chart builder where you pick a job_type field, a token sum, a date grouping, and a color, and the card lands on the dashboard.

You keep every guardrail AIKit gives you. The OpenAI key stays in the plugin settings, the per-user rate limits stay in place, and prompt templates still live in the AIKit screen. SleekView simply turns the existing job log into a configurable dashboard that editors, content leads, and finance can read at a glance.

AIKit lives where editors already work, right inside the Gutenberg sidebar, which is why it racks up so many small calls so quickly. The plugin records every one of them, but the built-in screen only lets you scroll through the log a row at a time. SleekView Charts treats the aikit_jobs table as a real dataset.

Editors get a daily generated-post area chart they can read in five seconds, content leads get a job-type donut that shows whether the team is leaning on write or rewrite, and finance gets a clean monthly token KPI that lines up with the OpenAI invoice. The key stays in AIKit, the prompt templates stay in AIKit, and the reporting finally lives where the writing actually happens.