for SEO generalists
discover candidate search topics, review in one approval queue, and send selected terms into a content plan for AutoSEO and publishing.
overview
this tool is designed to surface keyword opportunities you can act on and to move chosen terms directly into a content plan. it focuses on making discovery measurable and repeatable so your team spends time on execution rather than list management.
keyword research is in development. the current feature set emphasizes candidate generation and export to AutoSEO. the tool does not claim or display live search volume, difficulty, intent, clustering, or third-party ranking data until the grounding corpus verifies those signals.
how it fits your workflow
start with seeds from site content, git commits, social trends, or a target topic. generate candidate terms for human review and refine them in a single approval queue so every selected term is intentional and ready for content planning.
after approval, export terms into the AutoSEO blog engine or your content plan. drafting agents prepare outlines or full posts in your voice, and publishing follows your approval. for live rank data or volume metrics, use your existing rank tracker or external tools until the research module provides verified metrics.
capabilities
candidate generation that pulls from multiple inputs, a single approval queue for faster decisions, and direct export into a content plan. the process reduces handoffs and keeps your content pipeline moving from idea to draft.
the tool integrates with TTP AutoSEO and the MCP surface for drafting and publishing. while research metrics are being finalized, the workflow still speeds selection and handoff so your team can act on opportunities immediately.
evaluate fit
use qualitative signals and your own performance data to prioritize candidates while the research module matures. review relevance to user intent, alignment with existing content, and the practical effort to produce a useful page.
map approved terms into measurable experiments. set publishing dates, target outcomes, and the tracking method in your content plan so every term becomes a test you can measure with your rank tracker or analytics system.
vs manual spreadsheets
manual spreadsheets work for ad-hoc research but they add handoffs and delays. a research-to-content pipeline reduces copying, keeps approvals visible, and makes it easier to convert research into published content consistently.
a pipeline does not replace detailed audits. if you need deep, verified volume and ranking data today, continue using specialized tools. use the research workflow to accelerate selection and to feed your content engine once metrics are available or verified.
Questions for this workflow
keyword research is in development. the workflow components for candidate generation and export to AutoSEO exist in planned form. contact the product team for current availability and timeline if you need the feature in your workflow.
the tool does not provide live search volume, difficulty, intent, clustering, or third-party ranking data until those signals are verified by the grounding corpus. use your existing rank tracker or external sources for live metrics in the meantime.
after you approve terms in the single approval queue, export them directly to the AutoSEO blog engine or your content plan. agents can draft posts in your voice and queue content for publishing after your final approval.
use the tool to speed up discovery and reduce handoffs. collect seeds, generate candidates, review in one place, and export approved terms to your content plan. continue to use specialized analytics and rank data for measurement until the research module offers verified metrics.
Start with the workflow above, keep the human review gate, and adapt the cadence to the accounts you actually operate.
Start a review-first workflow